摘要:
A divider using neural network configurations comprises a subtractor, a selecting means, a first latch means, a second latch means, a shift register and a control means. The subtractor of the divider comprises plural inverters and plural 3-bit full-adders which are composed of four output lines, an input synapse group, a first bias synapse group, a second bias synapse group, a feedback synapse group, a neuron group and an inverter group.
摘要:
A divider circuit for efficiently and quickly performing a hardware implemented division by adopting a neural network architecture. The circuit includes a series of cascaded subtracter components that complement the divisor input and effectively perform an adder function. The subtracters include a synaptic configuration consisting of PMOS transistors, NMOS transistors, and CMOS inverters. The components are arranged in accordance with the predetermined connection strength assigned to each of the transistors and its respective position in the neural type network arrangement.
摘要:
Disclosed is a multi-layer neural network and circuit design method. The multi-layer neural network receiving an m-bit input and generating an n-bit output comprises a neuron having a cascaded pair of CMOS inverters and having an output node of the preceding CMOS inverter among the pair of CMOS inverters as its inverted output node and an output node of the succeeding CMOS inverter as its non-inverted output node, an input layer having m neurons to receive the m-bit input, an output layer having n neurons to generate the n-bit output, at least one hidden layer provided with n neurons to transfer the input received from the input layer to the directly upper hidden layer or the output layer, an input synapse group in a matrix having each predetermined weight value to connect each output of neurons on the input layer to each neuron of the output layer and at least one hidden layer, at least one transfer synapse group in a matrix having each predetermined weight value to connect each output of neurons of the hidden layer to each neuron of its directly upper hidden layer or of the output layer, and a bias synapse group for biasing each input node of neurons of the hidden layers and the output layer.
摘要:
A programmable multilayer neural network includes a weight storing circuit for storing the weight of each synapse to perform an intended function, an interfacing circuit for transmitting the weight value stored in the storing circuit to each synapse, and a multilayer neural network circuit programmed to have the weight from the weight storing circuit and for outputting an intended output.
摘要:
An error correction circuit is provided which uses NMOS and PMOS synapses to form neural network type responses to a coded multi-bit input. Use of MOS technology logic in error correction circuits allows such devices to be easily interfaced with other like technology circuits without the need to use distinct interface logic as with conventional error correction circuitry.
摘要:
A mapping circuit includes a linear circuit for outputting a signal which is linearly changed with respect to its input, a non-linear circuit for outputting a signal which is non-linearly changed with respect to its input, and an adder for summing the output signals of the linear and non-linear circuits and an external input signal. A chaotic neuron circuit using the mapping circuit has a simple structure and more precise chaos characteristics. A chaotic neural network can thus be formed by the serial and/or parallel interconnection of a plurality of chaotic neuron circuits, wherein the weight of each neuron is controlled.
摘要:
A synapse MOS transistor has gate electrodes of different lengths, different widths or different lengths and widths, between one source region and one drain region. Thus, when using the synapse MOS transistor to implement a neural network, the chip area can be greatly reduced.
摘要:
A chaotic recurrent neural network includes N chaotic neural networks for receiving an external input and the outputs of N-1 chaotic neural networks among said N chaotic neural networks and performing an operation according to the following dynamic equation ##EQU1## wherein W.sub.ij is a synapse connection coefficient of the feedback input from the "j"th neuron to the "i"th neuron, X.sub.i (t) is the output of the "i"th neuron at time t, and .gamma..sub.i, .alpha. and and k are a time-delaying constant, a non-negative parameter and a refractory time attenuation constant, respectively, and wherein Z.sub.i (t) represents X.sub.i (t) when i belongs to the neuron group I and represents a.sub.i (t) when i belongs to the external input group E. Also, a learning algorithm for the chaotic recurrent neural network increases its learning efficiency.
摘要:
A non-linear circuit includes a first variable resistor one end of which is applied with an input signal, an amplifier whose inverting input is connected to the other end of the first variable resistor and whose non-inverting input is connected to ground, a second variable resistor one end of which is connected to the inverting input of the amplifier, a third variable resistor one end of which is connected to the output of the amplifier and the other end being connected to the other end of the second variable resistor, and a fourth variable resistor one end of which is applied with the input signal and the other end being connected to the third variable resistor. A chaotic neuron circuit using the non-linear circuit includes a first sample-and-hold circuit for sampling the input signal in response to a first clock signal, a non-linear circuit for generating an output signal having a non-linear characteristic with respect to the output of the first sample-and-hold circuit, an adder for summing the output signal of the non-linear circuit and an external input signal, a second sample-and-hold circuit for sampling the output of the adder in response to a second clock signal and for outputting the result to the input of the first sample-and-hold circuit, and a clock generator for generating the first and second clock signals. The non-linear circuit and the chaotic neuron circuit using the same have a simple constitution.
摘要:
A priority encoder using a MOS array and neural network concepts is composed of an input side neuron group, an output side neuron group, a synapse group, a bias group and inverters. The encoder is simple in its construction and fast in its operating speed compared with the conventional priority encoders utilizing simple Boolean logic.