The present invention relates to an optical signal processing device that can be applied to optical reservoir computing.
In recent years, an environment has been constructed to acquire a large amount of data from various sensors via the Internet, and research and business for analyzing the large amount of acquired data and performing highly accurate knowledge processing and future prediction has been actively carried out. In general, because analysis of enormous data requires time and cost such as power consumption, a computing device having high speed and high efficiency is required. As a computing scheme for such information processing, an optical computing technique called reservoir computing (RC), which imitates signal processing of a cerebellum, has been proposed. Optical computing devices using a dynamical system are attracting attention because the devices are likely to have both high speed and high efficiency.
In an example of an application of optical RC in the related art, an example of solving a one-dimensional input and output problem such as a chaos approximation problem and NARMA10 has been mainly reported (for example, see Non Patent literature 1). Further, it is necessary to improve computing accuracy in order to further widen a range of applications of optical RC. In RC, it is generally known that the computing accuracy is improved by an increase in the number of nodes of a reservoir layer. However, in the case of optical RC, because the nodes of the reservoir layer are represented by the number of optical pulses that circulate around a fiber ring, a device having a longer fiber ring is required in order to increase the number of nodes and improve the computing accuracy.
Non Patent Literature 1: L. Larger, et al., “Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing,” Optics Express Vol. 20, Issue 3, pp. 3241-3249 (2012)
There are three problems when the fiber ring is lengthened. A first problem is an increase in manufacturing cost of a device. Because a price of a fiber is determined depending on the length, a cost of the fiber increases when the fiber ring is lengthened. A second problem is an increase in a size of the device. Because the fiber cannot be bent at an acute angle in view of loss, a volume for accommodation of the fiber increases when the fiber ring is lengthened. A third problem is unstable operation of the device. Because an optical pulse signal in the fiber easily changes due to an influence of a vibration or temperature change, an operating environment satisfying severe environmental conditions is required as the fiber ring is lengthened.
An object of the present invention is to provide an optical signal processing device capable of improving computing accuracy without increasing the number of nodes of a reservoir layer.
In order to achieve such an object, an aspect of the present invention is an optical signal processing device for converting an input one-dimensional signal to an optical signal and performing signal processing, the optical signal processing device including: an input unit configured to perform linear processing on the input one-dimensional signal to convert the one-dimensional signal to an optical signal; a reservoir unit connected to an output of the input unit and configured to perform linear processing and nonlinear processing on the optical signal; an output unit connected to an output of the reservoir unit and configured to convert the optical signal to an electrical signal, perform linear processing to output a one-dimensional output; and a determination unit configured to determine whether the one-dimensional output from the output unit is to be output or to be input as the one-dimensional signal to the input unit.
According to the present invention, a multi-layer structure in which a computing result calculated by optical RC is input to the input unit again is adopted by including the determination unit that is connected to the output unit and determines whether or not the output from the output unit is fed back as an input signal again, and it is possible to improve computing accuracy without increasing the number of nodes of a reservoir layer corresponding to one layer.
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
The optical signal processing device according to the embodiment adopts a multi-layer structure in which a computing result calculated by optical RC is input to the reservoir unit 12 again by including the determination unit 14 that determines whether or not the output from the output unit 13 is fed back as an input signal again, and it is possible to effectively increase the number of nodes and improve computing accuracy. In other words, it is possible to improve the computing accuracy without increasing the number of nodes in each reservoir unit using a device configuration in which the numbers of nodes of the reservoir units 12 are the same.
Input Unit
A case in which the input signal is distributed from one input channel to m nodes of the reservoir layer in normal RC is considered. Here, the input channel corresponds to a sampling number (voice data or the like) or the number of pixels (image data or the like) of one piece of data (which is represented as a pulse train in which one pulse is arranged in
A randomly determined weight winlm of the input unit is then multiplied with the extended time-series signal. A subscript 1 is a type of the one-dimensional signal in the first layer corresponding to the input channel, and is N in the second and subsequent layers. This allows a pulse extended to K seconds to be a modulation signal having different intensity for one second. An optical modulation unit 112 modulates an optical signal from a light source 113 with a modulation signal having information of winlm·um.
Thus, the input unit 11 outputs, to the reservoir unit 12, a pulse train in which K pulses having light intensity corresponding to a magnitude (intensity) of the input signal are connected by the number of 1 types of one-dimensional signals for each time step um.
For the light source 113, an incoherent light source or a coherent light source can be used. When the former is used, the light source can be operated relatively stably because only intensity information is used. When the latter is used, an amount of information can be doubled because both intensity information and phase information are used.
For the optical modulation unit 112, an optical attenuator such as an LN modulator or an optical amplifier such as a semiconductor optical amplifier can be used. When the former is used, it is possible to shorten a computing time because modulation can be performed at a high speed. When the latter is used, it is possible to curb deterioration of computing capability due to a loss because a signal can be amplified.
A weight win of the input unit is given before training of optical RC starts, and a value of the weight is not updated through training or a determination. All values of respective elements of the weight win (weight win≥0) may be different values, or may be the same value for the same m. Although the number of weights differs between the first layer and the second layer, the weights may be different or some of the weights may be the same.
Specific Operation Example
The one-dimensional signal is one-dimensional time-series data, such as a transition in a stock price of a certain company or a transition in temperature at a certain weather station. A case of utilization for temperature prediction in a specific weather station will be described herein.
Time-series data of temperature during a predetermined period of time is divided by certain periods of time, and data is created for each of the divided periods. For example, the predetermined period of time is divided into nine (1=9), and an average temperature during the divided period of time is calculated and used as the one-dimensional input signal. The signal processing unit 111 generates a time-series signal obtained by extending the one-dimensional input signal K-fold in order to perform processing m times in the reservoir unit 12, and multiplies the weight win of the input unit with the time-series signal to generate a modulation signal. The weight win may be a random value among K values.
The optical modulation unit 112 modulates the optical signal from the light source 113 with a modulation signal, outputs K optical pulses having different light intensities from one input signal, and combines all of the divided one-dimensional signals to output 9 K optical pulse trains.
Reservoir Unit
A dynamic system in the reservoir unit 12 is shown in Equation (1).
Math. 1
x
1(t)=cos2(ΣmKwlmin·um(t)+ΣkKwIkr·xk(t−1)) (1)
Here, um is a time step of the input unit 11 and corresponds to a node of the input layer, winlm represents a weight of the input unit, xk(t−1) corresponds to a node of the reservoir layer when a pulse circulates around the waveguide 124 t−1 times, wrik represents a weight of the reservoir unit, and x1 corresponds to m nodes of the reservoir layer. Among components input to a cos square function of Equation (1), a first term indicates a signal coupled from the input unit 11, and a second term indicates a signal coupled from the reservoir unit 12. A weight wr of the reservoir unit is a fixed value that is randomly determined, like the weight of the input unit. The optical computation processing unit 122 performs linear processing for multiplying the weight wr of the reservoir unit and nonlinear processing for performing computation of a nonlinear function (a cos square function). The weight wr of the reservoir unit is a fixed value that is randomly determined, as in the input unit.
For the optical computation processing unit 122, methods of performing linear processing include a method of using an LN modulator and a delay circuit, and a method of demodulating a signal with an electrical signal once, performing electrical computation processing using a PC, an FPGA, or the like, and then performing return to an optical signal. When the former is used, a processing speed becomes higher because the calculation is performed at the speed of light. When the latter is used, it is possible to ensure the computing accuracy because signal compensation can be performed when conversion to electricity is performed.
The optical computation processing unit 122 can use, for example, a Mach-Zehnder interferometer or a semiconductor optical amplifier in order to perform the nonlinear processing. When the former is used, power consumption is reduced because nonlinear processing is performed with only passage through the Mach-Zehnder interferometer without using a control signal. When the latter is used, it is possible to change a form of the nonlinear function from the cos square function by changing a current value injected into the semiconductor optical amplifier, and to perform adjustment to an appropriate nonlinear function for a problem to be solved.
For the merging unit 123, for example, a planar optical waveguide (PLC) or a fusion-extended fiber coupler can be used. When the former is used, it is possible to reduce a connection loss and construct a device with a low loss. When the latter is used, it is possible to easily construct the device by combining commercially available products.
Specific Operation Example
A specific operation example of the reservoir unit will be described with reference to
The ring waveguide 124 may be extended in length so that K or more pulses can circulate at the same time in consideration of extensibility. In this case, in the pulse train output from the input unit 11, an idle period of time corresponding to a time corresponding to the extended length is inserted into every K pulses. Thus, the temperature data divided in nine is processed by the m nodes of the reservoir layer.
Output Unit
A dynamic system in the output unit 13 is shown in Equation (2).
Math. 2
y
j(t)=kmwjko·xk(t) (2)
Here, yj corresponds to a node of the output layer, and wojk is a weight of the output unit. The electrical computation processing unit 132 extracts m of the one-dimensional signals xk(t) output from the demodulation unit at a time and calculates the linear combination shown in Equation (2). The calculation is repeated a number of times corresponding to the number N of categories to be classified, and N one-dimensional outputs are generated from m signals. A weight wo of the output unit is a value that is calculated by a pseudo-inverse matrix method using a node xk(t) of the reservoir unit and a desired result of the problem to be solved. This value is different for each layer.
For the demodulation unit 131, a light receiver is used. For the electrical computation processing unit 132, a PC and an FPGA, for example, can be used. When the former is used, it is possible to implement a dynamical system relatively easily. When the latter is used, it is possible to increase a computing speed because dedicated machine can be manufactured.
Specific Operation Example
In the reservoir unit 12, the temperature data divided in nine is processed by the m nodes of the reservoir layer. In the output unit 13, N candidate values for a transition in the predicted temperature are obtained from K pieces of data processed in the reservoir layer.
Determination Unit
The determination unit 14 determines whether the one-dimensional signal output from the output unit 13 is to be read as a computing result or to be propagated as an input signal to the input unit 11 again. For example, when data having a length of Linput seconds of the one-dimensional signal input to the input unit 11 is solved by RC of A layers, data up to Linput×(A−1) seconds after the signal first propagates to the determination unit 14 propagates to the input unit 11, and data after Linput×(A−1) seconds is read as a computing result.
For the determination unit 14, a switch can be used. An operation timing of the switch is synchronized with a device that generates the modulation signal of the input unit 11.
Specific Operation Example
As described above, in the first layer, the one-dimensional signal of the problem to be solved by the optical RC is input to the input unit 11, and in the A-th (1<A≤C) layer, the one-dimensional signal is first input to the deep optical RC and then the one-dimensional time-series signal propagating from the determination unit 14 is input at an (A−1)-th round. That is, the determination unit 14 causes the output from the output unit 13 to be input as a one-dimensional signal to the input unit 11 again when the number of times the output unit 13 performs output is smaller than A, and causes the output from the output unit 13 to be output as a one-dimensional output when the number of times the output unit 13 performs output is A. Thus, deep optical RC of the C layers is executed, and the most probable candidate value of the temperature is obtained in the temperature prediction.
With the optical signal processing device of the embodiment, it is possible to improve the computing accuracy using a device configuration in which the numbers of nodes are the same by adopting a multi-layer structure in which the computing result calculated by optical RC is input to optical RC again, instead of increasing the number of nodes. In optical RC in the related art, the number of nodes of the reservoir layer is increased so that the computing accuracy is improved, whereas in the embodiment, it is possible to improve the computing accuracy with the same number of nodes, it is not necessary to lengthen the fiber ring in the reservoir layer, and it is possible to curb a manufacturing cost of the device and reduce a size of the device. Further, in the embodiment, it is possible to stabilize an operation of the device because the computation can be performed with a short fiber ring.
Number | Date | Country | Kind |
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2018-155727 | Aug 2018 | JP | national |
Filing Document | Filing Date | Country | Kind |
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PCT/JP2019/031971 | 8/14/2019 | WO | 00 |