RESERVOIR COMPUTING APPARATUS AND DATA PROCESSING METHOD

    公开(公告)号:US20230244919A1

    公开(公告)日:2023-08-03

    申请号:US18097651

    申请日:2023-01-17

    CPC classification number: G06N3/063

    Abstract: At least one embodiment of the present disclosure provides a reservoir computing apparatus and a data processing method. The reservoir computing apparatus includes: a signal input circuit, configured to receive an input signal; a reservoir circuit, including a plurality of reservoir sub-circuits, in which each reservoir sub-circuit includes a mask sub-circuit and a rotating neuron sub-circuit, the mask sub-circuit is configured to perform a first processing on the input signal with a first weight to obtain a first processing result, and the rotating neuron sub-circuit is configured to perform a second processing on the first processing result to obtain a second processing result; and an output layer circuit, configured to multiply a plurality of second processing results by a second weight matrix to obtain a third processing result. The reservoir computing apparatus optimizes operation efficiency and reduces implementation costs.

    DATA PROCESSING APPARATUS AND DATA PROCESSING METHOD

    公开(公告)号:US20250005353A1

    公开(公告)日:2025-01-02

    申请号:US18695316

    申请日:2021-12-28

    Abstract: A data processing apparatus and a data processing method. The data processing apparatus includes: a bidirectional data processing module, including at least one storage and computing integration computing array; a controlling module, configured to switch a working mode of the bidirectional data processing module to an inference working mode to perform an inference computing task, and to switch the working mode of the bidirectional data processing module to a training working mode to perform a training computing task; a parameter management module, configured to set a weight parameter of the bidirectional data processing module; and an inputting and outputting module, configured to generate a computing inputting signal according to inputting data of the computing task, provide the computing inputting signal to the bidirectional data processing module, and receive a computing outputting signal from the bidirectional data processing module and generate outputting data according to the computing outputting signal.

    DATA PROCESSING METHOD BASED ON MEMRISTOR ARRAY AND ELECTRONIC APPARATUS

    公开(公告)号:US20240170060A1

    公开(公告)日:2024-05-23

    申请号:US17788408

    申请日:2021-12-14

    CPC classification number: G11C13/0069 G11C13/0026 G11C13/0028 G11C2213/79

    Abstract: A data processing method based on a memristor array and an electronic apparatus are disclosed. The data processing method based on a memristor array includes: acquiring a plurality of first analog signals; setting the memristor array, and writing data corresponding to a convolution parameter matrix of a convolution processing into the memristor array; inputting the plurality of first analog signals respectively into a plurality of column signal input terminals of the memristor array that has been set, controlling operation of the memristor array to perform the convolution processing on the plurality of first analog signals, and obtaining a plurality of second analog signals after performing the convolution processing at a plurality of row signal output terminals of the memristor array, respectively.

    MEMORY COMPUTING INTEGRATED DEVICE AND CALIBRATION METHOD THEREOF

    公开(公告)号:US20240320083A1

    公开(公告)日:2024-09-26

    申请号:US18574247

    申请日:2021-12-13

    CPC classification number: G06F11/0793 G06F11/073

    Abstract: A storage and computation integrated apparatus and a calibration method therefor. The storage and computation integrated apparatus includes a first processing unit, which includes: a first computation memristor array; a first calibration memristor array; and a first processing unit. The calibration method includes: determining, by means of off-chip training, a first computation weight matrix which corresponds to a first computation memristor array, and writing the first computation weight matrix into the first computation memristor array; and on the basis of the first computation memristor array where the first computation weight matrix has been written and the first computation weight matrix, performing on-chip training on a first calibration memristor array, so as to adjust a weight value of the first calibration memristor array.

    TRAINING METHOD OF NEURAL NETWORK BASED ON MEMRISTOR AND TRAINING DEVICE THEREOF

    公开(公告)号:US20220374688A1

    公开(公告)日:2022-11-24

    申请号:US17049349

    申请日:2020-03-06

    Abstract: A training method and a training device for a neural network based on memristors are provided. The neural network includes a plurality of neuron layers connected one by one and weight parameters between the plurality of neuron layers, and the training method includes: training the weight parameters of the neural network, and programming a memristor array based on the weight parameters after being trained to write the weight parameters after being trained into the memristor array; and updating a critical layer or several critical layers of the weight parameters of the neural network by adjusting conductance values of at least part of memristors of the memristor array.

    SIGNAL PROCESSING APPARATUS AND SIGNAL PROCESSING METHOD

    公开(公告)号:US20220061729A1

    公开(公告)日:2022-03-03

    申请号:US17412016

    申请日:2021-08-25

    Abstract: A signal processing apparatus and a signal processing method are provided. The signal processing apparatus includes a memristor array, an input circuit, a first switching circuit, a second switching circuit, an output circuit, and a control circuit. The memristor array includes memristor units and is connected to source lines, word lines and bit lines. The control circuit is configured to control the first switching circuit to select at least one source line to apply at least one first signal to the at least one source line respectively, control the second switching circuit to select and activate at least one word line to apply the at least one first signal to a memristor unit corresponding to the at least one word line, and control the output circuit to output a plurality of second signals based on conductivity values of memristors of the memristor array.

    NANOWIRE TRANSISTOR AND MANUFACTURING METHOD THEREOF

    公开(公告)号:US20210184025A1

    公开(公告)日:2021-06-17

    申请号:US17058211

    申请日:2018-08-03

    Abstract: A nanowire transistor and a manufacture method thereof are provided. The nanowire transistor includes a semiconductor wire, a semiconductor layer, a source electrode and a drain electrode. The semiconductor wire includes a first semiconductor material and includes a source region, a drain region, and a channel region, along an axial direction of the semiconductor wire, the channel region is between the source region and the drain region; the semiconductor layer includes a second semiconductor material and covers the channel region of the semiconductor wire; the source electrode is in the source region of the semiconductor wire and is in direct contact with the source region of the semiconductor wire, and the drain electrode is in the drain region of the semiconductor wire and is in direct contact with the drain region of the semiconductor wire.

    DATA PROCESSING METHOD BASED ON MEMRISTOR ARRAY, AND ELECTRONIC APPARATUS

    公开(公告)号:US20250078924A1

    公开(公告)日:2025-03-06

    申请号:US18726931

    申请日:2022-01-11

    Abstract: At least one embodiment of the present disclosure provides a data processing method based on a memristor array and an electronic apparatus. The data processing method includes: acquiring a plurality of first analog signals; setting the memristor array, and writing data of a parameter matrix corresponding to the data processing into the memristor array; and inputting the plurality of first analog signals into a plurality of column signal input terminals of the set memristor array, respectively, controlling operation of the memristor array to perform the data processing on the plurality of first analog signals, and obtaining a plurality of second analog signals after performing the data processing at a plurality of row signal output terminals of the memristor array, respectively.

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