Spike neural network circuit, stdp learning circuit, and operation method of stdp learning circuit

A spike-timing dependent plasticity (STDP) learning circuit comprising:

• a timer configured to output a time value that increases over time;
• a plurality of input time registers corresponding to each of a plurality of row lines of a synapse array and configured to store the time value that the timer outputs when an input spike signal occurs on the corresponding row line;
• a plurality of output time registers corresponding to each of a plurality of column lines of the synapse array and configured to store the time value that the timer outputs when an output spike signal occurs on the corresponding column line;
• a time difference calculator configured to calculate an occurrence time difference between occurrence of the output spike signal and occurrence of the input spike signal;
• a weight update circuit configured to update, in response to occurrence of the input spike signal or occurrence of the output spike signal, a weight value of the corresponding synapse circuits included in the synapse array based on a weight change amount corresponding to the occurrence time difference;
• and
• a control circuit configured to control operation of the timer, the plurality of input time registers, the plurality of output time registers, the time difference calculator, and the weight update circuit.

An operation method of a spike-timing dependent plasticity (STDP) learning circuit, the operation method comprising:

• receiving an output spike signal from one of a plurality of columns;
• writing an occurrence time of the output spike signal into an output time register corresponding to a column line in which the output spike signal occurred;
• initializing an output overflow register corresponding to the output spike signal;
• obtaining an occurrence time of an input spike signal written in an input time register for each of a plurality of row lines;
• calculating an occurrence time difference between the occurrence time of the output spike signal and the occurrence time of the input spike signal for each of the plurality of row lines;
• obtaining a weight change amount according to the time difference for each of the plurality of row lines;
• obtaining a weight value for each of the synapse circuits corresponding to the column line in which the output spike signal occurred;
• and
• updating the weight value of each of the corresponding synapse circuits in the column line in which the output spike signal occurred by applying the weight change amount to each of the corresponding synapse circuits.