Hitachi, Ltd.

Hidenori Inouchi

Toru Baji

Masakazu Ejiri

Kazuaki Iwamura

Shigeru Kakumoto

A neural net signal processor provided with a single layer neural net constituted of N neuron circuits which sums the results of the multiplication of each of N input signals Xj(j=1 to N) by a coefficient mij to produce a multiply-accumulate value ##EQU1## thereof, in which input signals Xj(j=1 to N) for input to the single layer neural net are input as serial input data, comprising: a multiplicity of systolic processor elements SPE-1(i=1 to M), each comprised of a two-state input data delay latch; a coefficient memory; means for multiplying and summing for multiply-accumulate output operations; an accumulator; a multiplexor for selecting a preceding stage multiply-accumulate output Sk(k=1 to i-1) and the multiply-accumulate product Si computed by the said circuit; wherein the multiplicity of systolic processor elements are serially connected to form an element array and element multiply-accumulate output operations are executed sequentially to obtain the serial multiply-accumulate outputs Si(i=1 to M) of one layer from the element array.

Systolic processor elements for a neural network

A data communication apparatus comprises: means for dividing data to be transmitted into a plurality of blocks and extracting the data from each block; a first multi-layered neural network of three or more layers which has weighting coefficients to output the same data as the input data for the data extracted from each block and which can output data from an intermediate layer; the transmission data extracted from each block being inputted to the first neural network and outputted from the intermediate layer; means for encoding the transmission data which is outputted from the intermediate layer of the first neural network and, thereafter, transmitting; means for receiving and decoding the transmitted data; a second multi-layered neural network of three or more layers which has the same weight coefficients as those of the first neural network and can input data from an intermediate layer; the decoded data of each block being inputted to the second neural network and outputted from an output layer; and means for restoring the data on the basis of the output data from the output layer of the second neural network.

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Hidenori Inouchi