Title :
Analogue circuit realization of a programmable sigmoidal function and its derivative for on-chip BP learning
Author :
Lu, Chun ; Shi, Bingxue ; Chen, Lu
Author_Institution :
Inst. of Microelectron., Tsinghua Univ., Beijing, China
Abstract :
In an on-chip Back-Propagation (BP) algorithm learning neuron, both the sigmoidal activation function and its derivative are needed. A novel analog circuit is proposed, which can realize both functions. The neuron can be adapted to various environments by programming the threshold and the gain factor of the sigmoidal function. The nonlinear partition problem is used to verify the operation of the proposed circuit
Keywords :
CMOS analogue integrated circuits; analogue processing circuits; backpropagation; neural chips; programmable circuits; ANN; analogue circuit realization; backpropagation algorithm; nonlinear partition problem; onchip BP learning neuron; programmable gain factor; programmable sigmoidal function; programmable threshold; sigmoidal activation function; sigmoidal activation function derivative; Analog circuits; Artificial neural networks; Concurrent computing; Functional programming; Microelectronics; Network-on-a-chip; Neural networks; Neurons; Partitioning algorithms; Voltage;
Conference_Titel :
Circuits and Systems, 2000. IEEE APCCAS 2000. The 2000 IEEE Asia-Pacific Conference on
Conference_Location :
Tianjin
Print_ISBN :
0-7803-6253-5
DOI :
10.1109/APCCAS.2000.913579
