CN109302238B - Parameter adjusting method and system for optical IQ modulator - Google Patents
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Abstract
A parameter adjusting method and system for an optical IQ modulator relates to an optical fiber communication system, and the method comprises the following steps: establishing a neural network by utilizing a simulation mode, and enabling each channel equalization parameter to form mapping with a group of adjusting parameters of the dual-polarization IQ modulator; coupling an optical signal output by the dual-polarization IQ modulator after signal loading with another optical carrier signal, wherein the optical carrier signal is positioned at the edge of an optical signal spectrum, and the optical signal after wave combination is subjected to polarization beam splitting to respectively realize photoelectric conversion and sampling; changing the sampling signal into an over-sampling signal of 2 times, and then carrying out channel estimation to obtain a channel equalization parameter and input the channel equalization parameter into the neural network, wherein the neural network outputs a corresponding group of adjusting parameters; the set of tuning parameters is used to modulate a dual-polarization IQ modulator. The invention can accurately output each adjusting parameter of the dual-polarization IQ modulator to be adjusted, so as to facilitate subsequent simultaneous adjustment, and improve the adjusting efficiency and the adjusting accuracy.
Description
Technical Field
The present invention relates to an optical fiber communication system, and in particular, to a method and a system for adjusting parameters of an optical IQ modulator.
Background
As the demand for traffic in optical fiber communication networks continues to increase, optical fiber communication systems based on coherent technologies have gained more and more attention. In an optical fiber communication system based on coherent optical technology, a dual-polarization IQ modulator is one of the key devices for implementing amplitude and phase mapping, and the consistency of the I-path (real part) and Q-path (imaginary part) electrical signals loaded to two polarization states can seriously affect the performance of the coherent optical communication system. The consistency of the dual-polarization IQ modulator is mainly represented by the consistency of the amplitude and the time delay of the I path signal and the Q path signal on a single polarization state, and the consistency of the amplitude and the time delay between the dual-polarization electric signals.
As shown in fig. 1, the existing solution is to input the optical signal output by the dual-polarization IQ modulator and the continuous light emitted by another laser into the integrated coherent optical receiving module. In the conventional coherent light reception mode, the frequency of light emitted from the laser 2 is similar to that of light emitted from the laser 1, and coherent reception is performed by means of interpolation. The integrated coherent light receiving module can output electric signals on two polarization states, measure and calculate the quality factor of each electric signal, and when the quality factor reaches the maximum, the recovery quality of the signal is considered to be the best, so the quality factor can reach the maximum only by adjusting the adjusting parameters of the dual-polarization IQ modulator.
Because the adjustment result is judged according to the output of the integrated coherent light receiving module, the adjustment degree of the deviation on the dual-polarization IQ modulator cannot be known in the whole adjustment process. And the adjustment parameters of the dual-polarization IQ modulator comprise: the real and imaginary amplitude ratio of the X polarization electrical signal, the real and imaginary amplitude ratio of the Y polarization electrical signal, the real and imaginary time difference of the X polarization electrical signal, the real and imaginary time difference of the Y polarization electrical signal, the time difference of the X polarization and the Y polarization real part, the time difference of the X polarization and the Y polarization imaginary part, the amplitude ratio of the X polarization and the Y polarization real part, and the amplitude ratio of the X polarization and the Y polarization imaginary part. During adjustment, each adjustment parameter needs to be debugged trial and error respectively, which results in long adjustment time and low efficiency. In addition, the deviation of the amplitude and time of the electrical signal exists not only on the dual-polarization IQ modulator, but also in the integrated coherent optical receiving module, and due to the joint debugging, even if the output quality factor reaches the best, the adjustment parameters of the dual-polarization IQ modulator cannot be guaranteed to be adjusted to the best, so that the adjustment is not accurate enough.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a parameter adjusting method and a parameter adjusting system for an optical IQ modulator, which are used for accurately outputting each adjusting parameter to be adjusted by a dual-polarization IQ modulator so as to facilitate subsequent simultaneous adjustment and improve the adjusting efficiency and the adjusting accuracy.
In order to achieve the above object, in one aspect, a method for adjusting parameters of an optical IQ modulator is adopted, including:
establishing a neural network by utilizing a simulation mode, and enabling each channel equalization parameter to form mapping with a group of adjusting parameters of the dual-polarization IQ modulator;
coupling an optical signal output by the dual-polarization IQ modulator after signal loading with another optical carrier signal, wherein the optical carrier signal is positioned at the edge of an optical signal spectrum, and the optical signal after wave combination is subjected to polarization beam splitting to respectively realize photoelectric conversion and sampling;
changing the sampling signal into an over-sampling signal of 2 times, and then carrying out channel estimation to obtain a channel equalization parameter and input the channel equalization parameter into the neural network, wherein the neural network outputs a corresponding group of adjusting parameters;
the set of tuning parameters is used to modulate a dual-polarization IQ modulator.
Preferably, the channel equalization parameters are input to the neural network in a matrix form, and the establishing a neural network by using a simulation mode includes: and respectively setting a plurality of groups of adjusting parameters as training data, carrying out channel equalization on the simulation signals according to different conditions to obtain channel equalization parameters under different conditions, and storing the channel equalization parameters by using a matrix, wherein the row number in the matrix represents the group number of the training data, and the column number represents the length of the characteristic vector of the neural network.
Preferably, the neural network is a full-link type neural network, and includes four layers:
the first layer is an input layer and comprises the number of neurons which is the same as the column number of the matrix of the channel equalization parameters;
the second layer and the third layer are hidden layers and respectively comprise a plurality of neurons, and the activation function of the hidden layer is a scaling exponential linear function;
the fourth layer is an output layer, the activation function of the output layer is a scaling exponential linear function, and the fourth layer comprises a plurality of neurons and corresponds to a group of adjusting parameters of the dual-polarization IQ modulator.
Preferably, the set of adjustment parameters includes: the real and imaginary amplitude ratio of the X polarization electrical signal, the real and imaginary amplitude ratio of the Y polarization electrical signal, the real and imaginary time difference of the X polarization electrical signal, the real and imaginary time difference of the Y polarization electrical signal, the time difference of the X polarization and the Y polarization real part, the time difference of the X polarization and the Y polarization imaginary part, the amplitude ratio of the X polarization and the Y polarization real part, and the amplitude ratio of the X polarization and the Y polarization imaginary part.
Preferably, when the real part and the imaginary part of the X polarization electric signal are adjusted to be consistent and the real part and the imaginary part of the Y polarization electric signal are adjusted to be consistent, the time difference of the real part of the X polarization and the time difference of the imaginary part of the Y polarization are equal to the time difference of the real part of the X polarization and the time difference of the imaginary part of the Y polarization; the amplitude ratio of the real part of the X polarization to the imaginary part of the Y polarization is equal to the amplitude ratio of the imaginary part of the X polarization to the Y polarization; in the set of adjustment parameters, the time difference between the X polarization and the Y polarization is only represented by one parameter, and the amplitude ratio of the X polarization and the Y polarization is only represented by one parameter.
In another aspect, an optical IQ modulator parameter adjustment system is adopted, including:
a dual-polarization IQ modulator for IQ modulating the analog electrical signal;
two lasers, one of which is used to provide an optical carrier for the single polarization IQ modulator and the other is used to provide an optical carrier at the spectral edge of the optical signal;
a coupler for coupling a dual-polarization IQ modulator output optical signal with an optical carrier emitted by the other laser;
the polarization beam splitter is used for splitting the coupled optical signals into two paths with mutually vertical polarization states;
the two photoelectric detectors are used for respectively receiving the optical signals output by the polarization divider and realizing photoelectric conversion;
the real-time oscilloscope is used for sampling the electric signals output by the two photoelectric detectors and converting the electric signals into digital signals;
and the digital signal processor is used for calculating the channel equalization parameters of the sampling digital signals of the real-time oscilloscope, and calculating and outputting a group of adjusting parameters of the dual-polarization IQ modulator through a neural network.
Preferably, the digital signal processor includes:
a resampling module for changing the received signal into an oversampled signal of 2 times;
the beat frequency noise preprocessing module is used for reducing the beat frequency noise of the two polarization signals;
the channel estimation module is used for carrying out channel estimation on the dual-polarization signal to obtain a channel equalization parameter;
and the neural network module is used for establishing a mapping relation between each channel equalization parameter and a group of adjusting parameters through the neural network, receiving the channel equalization parameters and outputting a group of adjusting parameters.
Preferably, the channel equalization parameters in the neural network are stored in a matrix, wherein rows of the matrix represent the number of groups of training data or the number of groups of data to be measured, and columns of the matrix represent the length of the characteristic vector of the neural network.
Preferably, the neural network is a full-link type neural network, and includes four layers:
the first layer is an input layer and comprises the number of neurons which is the same as the column number of the matrix of the channel equalization parameters;
the second layer and the third layer are hidden layers and respectively comprise a plurality of neurons, and the activation function of the hidden layer is a scaling exponential linear function;
the fourth layer is an output layer, the activation function of the output layer is a scaling exponential linear function, and the fourth layer comprises a plurality of neurons and corresponds to a group of adjusting parameters of the dual-polarization IQ modulator.
Preferably, the set of adjustment parameters includes:
the real part and imaginary part amplitude ratio of the X-polarized electrical signal, the real part and imaginary part amplitude ratio of the Y-polarized electrical signal, the real part and imaginary part time difference of the X-polarized electrical signal, and the real part and imaginary part time difference of the Y-polarized electrical signal;
further comprising: the time difference of the real parts of the X polarization and the Y polarization, and/or the time difference of the imaginary parts of the X polarization and the Y polarization;
further comprising: the ratio of the magnitudes of the real parts of the X-polarization and the Y-polarization, and/or the ratio of the magnitudes of the imaginary parts of the X-polarization and the Y-polarization.
One of the above technical solutions has the following beneficial effects:
1. the method adopts a heterodyne detection mode, an integrated coherent light receiving module is not used in the system, and the deviation caused by the traditional coherent light receiving is avoided, so that the influence of inconsistency brought by a frequency mixer in the coherent light receiving is eliminated, a group of adjusting parameters (namely the degree of inconsistency of electric signals) can be accurately extracted, the dual-polarization IQ modulator can be conveniently adjusted subsequently and simultaneously, and the adjusting efficiency and the adjusting accuracy are improved.
2. In the digital signal processing, channel equalization parameters are obtained after channel equalization, and the parameters include the working state of the IQ modulator, so that a group of adjusting parameters can be output, and the accurate adjustment of the dual-polarization IQ modulator is facilitated.
3. A neural network is adopted in the digital signal processing, and a mapping relation is formed between each channel equalization parameter and a group of adjusting parameters of the dual-polarization IQ modulator in a machine learning mode, so that the estimation and the output of the adjusting parameters are realized.
Drawings
Fig. 1 is a diagram of a parameter measurement architecture of a dual-polarization IQ modulator in the related art.
FIG. 2 is a flow chart of a parameter adjusting method for an optical IQ modulator according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an optical IQ modulator parameter adjustment system according to an embodiment of the present invention;
fig. 4 is a schematic diagram of internal blocks of the digital signal processor shown in fig. 3.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
As shown in fig. 2, the present embodiment provides a method for adjusting parameters of an optical IQ modulator, comprising the steps of:
s1, establishing a neural network by using a simulation mode, and enabling each channel equalization parameter to form mapping with a group of adjusting parameters of the dual-polarization IQ modulator.
And S2, coupling the optical signal output by the dual-polarization IQ modulator after signal loading with another optical carrier signal, wherein the optical carrier signal is positioned at the edge of an optical signal frequency spectrum.
And S3, carrying out polarization beam splitting on the coupled signals, and respectively realizing photoelectric conversion to obtain electric signals.
And S4, sampling the converted electric signal in real time and converting the electric signal into a digital signal.
And S5, resampling the digital signal obtained after sampling to obtain an oversampled signal of 2 times.
And S6, performing channel estimation on the oversampled dual-polarization signal by adopting a traditional channel estimation algorithm to obtain channel equalization parameters. Wherein, the channel equalization parameters are expressed by adopting a matrix mode. The number of rows in the matrix represents the number of sets of training data and the number of columns represents the length of the neural network eigenvector. For example, the channel equalization parameters are represented in a matrix form of M × 9, where M represents the number of groups of data to be measured, and 9 is the length of the channel equalization parameters.
And S7, inputting the obtained channel equalization parameters into the established neural network, and outputting a corresponding group of adjusting parameters by the neural network.
And S8, adopting the set of adjusting parameters to simultaneously modulate the dual-polarization IQ modulator.
In the step S1, the establishing the neural network in the simulation mode specifically includes:
respectively setting a plurality of groups of adjusting parameters, for example, setting the amplitude ratio of the real part and the imaginary part of the X-polarization electric signal to be 1.0, 1.1, 1.2 and 1.3 respectively; time differences of the real part and the imaginary part of the X-polarized electric signal are set to 0ps, 5ps, 10ps, 15ps and 20ps, respectively. The simulated signal in this embodiment adopts QPSK modulation format, and the digital-to-analog conversion rate is set at 10 GSa/s.
In the simulation process, aiming at different conditions (namely different groups of adjusting parameters), channel equalization is carried out on the simulation signals to obtain channel equalization parameters under different conditions, and the channel equalization parameters are stored in a matrix. Preferably, the channel equalization parameters are stored in a matrix form of N × 9, where N represents the number of sets of training data and 9 represents the length of the channel equalization parameters, i.e., the length of the neural network eigenvectors.
Preferably, the neural network is a fully-linked neural network, and comprises four layers:
the first layer is an input layer and comprises the number of neurons which is the same as the column number of the matrix of the channel equalization parameters; the first layer in this example consists of 9 neurons.
The second layer and the third layer are hidden layers, each of which comprises a plurality of neurons, and the activation function of the hidden layer is a Scaled exponential linear unit (SeLU). The number of neurons in the hidden layer is not specified, and may be determined by specific analysis according to training data, and in the machine learning process of the neural network, the number of neurons in the hidden layer is determined by that an error between an output value and a training target value converges and is smaller than a certain threshold, where the threshold may be preset according to an actual situation, and for a normalized training target value, the threshold may be usually set to 0.01. In this embodiment, the second layer includes 60 neurons, and the third layer includes 30 neurons.
The fourth layer is an output layer, the activation function of the fourth layer is a scaling exponential linear function (PReLU), the fourth layer comprises a plurality of neurons, each neuron corresponds to one output, and all the neurons correspond to one group of adjusting parameters of the dual-polarization IQ modulator.
The set of tuning parameters includes: the real and imaginary amplitude ratio of the X polarization electrical signal, the real and imaginary amplitude ratio of the Y polarization electrical signal, the real and imaginary time difference of the X polarization electrical signal, the real and imaginary time difference of the Y polarization electrical signal, the time difference of the X polarization and the Y polarization real part, the time difference of the X polarization and the Y polarization imaginary part, the amplitude ratio of the X polarization and the Y polarization real part, and the amplitude ratio of the X polarization and the Y polarization imaginary part.
In the output layer of the neural network, there may be 8 neurons, and each of the adjustment parameters is output correspondingly.
When the real part and the imaginary part of the X polarization electric signal are adjusted to be consistent, and the real part and the imaginary part of the Y polarization electric signal are adjusted to be consistent, the time difference of the real part of the X polarization and the time difference of the imaginary part of the Y polarization are equal to the time difference of the imaginary part of the X polarization; the ratio of the magnitude of the real part of the X-polarization to the magnitude of the imaginary part of the Y-polarization is equal to the ratio of the magnitude of the imaginary part of the X-polarization to the magnitude of the imaginary part of the Y-polarization. Therefore, the output layer may have only 6 neurons, corresponding to 6 output parameters, and the time difference between the X polarization and the Y polarization is represented by only one parameter, and the time difference between the real part and the imaginary part may be selected; the amplitude ratio of the X-polarization and the Y-polarization is represented by only one parameter, and the time difference of the real part and the time difference of the imaginary part can be selected, 6 neurons are shown in fig. 2, and 6 adjustment parameters are output.
As shown in fig. 3, the present embodiment provides a parameter adjusting system for an optical IQ modulator, which includes a dual-polarization IQ modulator, two lasers, a coupler, a polarization beam splitter, two photodetectors, a real-time oscilloscope, and a digital signal processor.
A dual-polarization IQ modulator for IQ modulating the analog electrical signal after analog-to-digital conversion.
The two lasers are divided into a first laser modulator and a second laser modulator, the first laser modulator is used for providing an optical carrier for the dual-polarization IQ modulator, and the dual-polarization IQ modulator outputs an optical signal loaded by the signal. The second laser modulator is used to provide an optical carrier at the edge of the optical signal spectrum.
A coupler for coupling the dual polarization IQ modulator output optical signal with an optical carrier emitted by the second laser modulator.
And the polarization beam splitter is used for splitting the coupled optical signal into two paths of optical signals with mutually vertical polarization states.
The two photoelectric detectors receive one path of optical signal divided by the polarization beam splitter respectively and convert the optical signal into an electric signal.
And implementing an oscilloscope, wherein the oscilloscope is used for receiving the converted electric signals, sampling the electric signals, converting the electric signals into digital signals and storing the digital signals.
And the digital signal processor is used for calculating the channel equalization parameters of the digital signal sampled by the oscilloscope, and calculating and outputting a group of adjusting parameters of the dual-polarization IQ modulator through the neural network so as to facilitate subsequent adjustment.
As shown in fig. 4, the digital signal processor further includes a resampling module, a beat noise preprocessing module, a channel estimation module, and a neural network module.
And the resampling module is used for resampling the two polarization signals received by the digital signal processor into 2-time oversampled signals.
And the beat frequency noise preprocessing module is used for reducing the beat frequency noise of the two polarization signals. This is because the optical carrier is located at the edge of the optical signal spectrum, and thus beat noise is introduced, and therefore, the optical carrier needs to be processed by the beat noise preprocessing module.
And the channel estimation module is used for performing channel estimation on the dual-polarization signal processed by the beat frequency noise preprocessing module through a traditional channel estimation algorithm to obtain channel equalization parameters. The channel equalization parameters are expressed in a matrix mode, the row number of the channel equalization parameters represents the group number of training data, and the column number of the channel equalization parameters represents the length of the characteristic vector of the neural network.
The neural network module establishes a neural network in advance through simulation, the mode of establishing the neural network is the same as the step S1 in the parameter adjusting method of the optical IQ modulator, a mapping relation between each channel equalization parameter and a group of adjusting parameters is established in the neural network, the channel equalization parameters obtained by the channel estimation module are received, and the mapped group of adjusting parameters are output.
In this embodiment, the neural network is the same as the previous embodiment, and is also a fully-linked neural network, and the number of internal layers and functions are also the same as those in the above-described embodiment.
In this embodiment, as in the previous embodiment, the set of adjusting parameters may be 8 or 6, and include time differences of real and imaginary parts of X-polarization and Y-polarization and/or time differences of imaginary and X-polarization in addition to the real and imaginary amplitude ratios of the X-polarized electrical signal, the real and imaginary amplitude ratios of the Y-polarized electrical signal, the real and imaginary time differences of the X-polarized electrical signal, and the real and imaginary time differences of the Y-polarized electrical signal; further comprising: the ratio of the magnitudes of the real parts of the X-polarization and the Y-polarization, and/or the ratio of the magnitudes of the imaginary parts of the X-polarization and the Y-polarization.
The present invention is not limited to the above-described embodiments, and it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements are also considered to be within the scope of the present invention. Those not described in detail in this specification are within the skill of the art.
Claims (8)
1. An optical IQ modulator parameter adjustment method, comprising:
establishing a neural network by utilizing a simulation mode, and enabling each channel equalization parameter to form mapping with a group of adjusting parameters of the dual-polarization IQ modulator;
coupling an optical signal output by the dual-polarization IQ modulator after signal loading with another optical carrier signal, wherein the optical carrier signal is positioned at the edge of an optical signal spectrum, and the optical signal after wave combination is subjected to polarization beam splitting to respectively realize photoelectric conversion and sampling;
changing the sampling signal into an over-sampling signal of 2 times, and then carrying out channel estimation to obtain a channel equalization parameter and input the channel equalization parameter into the neural network, wherein the neural network outputs a corresponding group of adjusting parameters;
modulating a dual-polarization IQ modulator by using the set of adjusting parameters;
the neural network is a full-link type neural network and comprises four layers:
the first layer is an input layer and comprises the number of neurons which is the same as the column number of the matrix of the channel equalization parameters;
the second layer and the third layer are hidden layers and respectively comprise a plurality of neurons, and the activation function of the hidden layer is a scaling exponential linear function;
the fourth layer is an output layer, the activation function of the output layer is a scaling exponential linear function, and the fourth layer comprises a plurality of neurons and corresponds to a group of adjusting parameters of the dual-polarization IQ modulator.
2. The method for parameter adjustment of an optical IQ modulator according to claim 1 wherein the channel equalization parameters are input to the neural network in the form of a matrix, the establishing the neural network by means of simulation comprising:
and respectively setting a plurality of groups of adjusting parameters as training data, carrying out channel equalization on the simulation signals according to different conditions to obtain channel equalization parameters under different conditions, and storing the channel equalization parameters by using a matrix, wherein the row number in the matrix represents the group number of the training data, and the column number represents the length of the characteristic vector of the neural network.
3. Optical IQ-modulator parameter adjustment method according to any of claims 1-2, characterized in that the set of adjustment parameters comprises:
the real and imaginary amplitude ratio of the X polarization electrical signal, the real and imaginary amplitude ratio of the Y polarization electrical signal, the real and imaginary time difference of the X polarization electrical signal, the real and imaginary time difference of the Y polarization electrical signal, the time difference of the X polarization and the Y polarization real part, the time difference of the X polarization and the Y polarization imaginary part, the amplitude ratio of the X polarization and the Y polarization real part, and the amplitude ratio of the X polarization and the Y polarization imaginary part.
4. The optical IQ modulator parameter adjustment method according to claim 3, characterized in that: when the real part and the imaginary part of the X polarization electric signal are adjusted to be consistent, and the real part and the imaginary part of the Y polarization electric signal are adjusted to be consistent, the time difference of the real part of the X polarization and the time difference of the imaginary part of the Y polarization are equal to the time difference of the imaginary part of the X polarization; the amplitude ratio of the real part of the X polarization to the imaginary part of the Y polarization is equal to the amplitude ratio of the imaginary part of the X polarization to the Y polarization;
in the set of adjustment parameters, the time difference between the X polarization and the Y polarization is only represented by one parameter, and the amplitude ratio of the X polarization and the Y polarization is only represented by one parameter.
5. An optical IQ modulator parameter adjustment system, comprising:
a dual-polarization IQ modulator for IQ modulating the analog electrical signal;
two lasers, one of which is used to provide an optical carrier for the dual polarization IQ modulator and the other is used to provide an optical carrier at the spectral edge of the optical signal;
a coupler for coupling the dual-polarization IQ modulator output optical signal with an optical carrier emitted by another laser;
the polarization beam splitter is used for splitting the coupled optical signals into two paths with mutually vertical polarization states;
the two photoelectric detectors are used for respectively receiving the optical signals output by the polarization beam splitter and realizing photoelectric conversion;
the real-time oscilloscope is used for sampling the electric signals output by the two photoelectric detectors and converting the electric signals into digital signals;
the digital signal processor is used for calculating channel equalization parameters of the sampling digital signals of the real-time oscilloscope, and calculating and outputting a group of adjusting parameters of the dual-polarization IQ modulator through a neural network;
the digital signal processor includes:
a resampling module for changing the received signal into an oversampled signal of 2 times;
the beat frequency noise preprocessing module is used for reducing the beat frequency noise of the two polarization signals;
the channel estimation module is used for carrying out channel estimation on the dual-polarization signal to obtain a channel equalization parameter;
and the neural network module is used for establishing a mapping relation between each channel equalization parameter and a group of adjusting parameters through the neural network, receiving the channel equalization parameters and outputting a group of adjusting parameters.
6. The optical IQ modulator parameter adjustment system according to claim 5, characterized in that: the channel equalization parameters in the neural network are stored in a matrix, wherein the rows of the matrix represent the group number of training data or the group number of data to be tested, and the columns of the matrix represent the length of the characteristic vector of the neural network.
7. The optical IQ modulator parameter adjustment system according to claim 6, characterized in that the neural network is a fully linked neural network comprising four layers:
the first layer is an input layer and comprises the number of neurons which is the same as the column number of the matrix of the channel equalization parameters;
the second layer and the third layer are hidden layers and respectively comprise a plurality of neurons, and the activation function of the hidden layer is a scaling exponential linear function;
the fourth layer is an output layer, the activation function of the output layer is a scaling exponential linear function, and the fourth layer comprises a plurality of neurons and corresponds to a group of adjusting parameters of the dual-polarization IQ modulator.
8. Optical IQ-modulator parameter adjustment system according to any of claims 5-7, characterized in that the set of adjustment parameters comprises:
the real part and imaginary part amplitude ratio of the X-polarized electrical signal, the real part and imaginary part amplitude ratio of the Y-polarized electrical signal, the real part and imaginary part time difference of the X-polarized electrical signal, and the real part and imaginary part time difference of the Y-polarized electrical signal;
further comprising: the time difference of the real parts of the X polarization and the Y polarization, and/or the time difference of the imaginary parts of the X polarization and the Y polarization;
further comprising: the ratio of the magnitudes of the real parts of the X-polarization and the Y-polarization, and/or the ratio of the magnitudes of the imaginary parts of the X-polarization and the Y-polarization.
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