Title :
CNN models of current mode neuromorphic networks
Author_Institution :
Dept. of Electr. & Electron. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
Abstract :
This paper describes the use of the cellular neural network model in understanding the operation of current mode neuromorphic networks consisting of subthreshold MOS transistors. The original proof of stability for symmetric cellular neural networks relied upon the definition of a suitable Lyapunov function. Here we show that Lyapunov functions can be defined for arbitrary networks of subthreshold MOS transistors operating as diffusers or pseudo-conductances and for the winner-take-all circuit of Lazzaro. We also derive an expression for the resolution of the winner-take-all circuit
Keywords :
Lyapunov methods; MOSFET circuits; cellular neural nets; circuit stability; current-mode circuits; neural chips; Lyapunov function; cellular neural network model; current-mode neuromorphic network; diffuser; pseudo-conductance; resolution; stability; subthreshold MOS transistor; winner-take-all circuit; Capacitors; Cellular neural networks; Circuit stability; Current measurement; Lyapunov method; MOSFETs; Neuromorphics; Q measurement; Resistors; Voltage;
Conference_Titel :
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6685-9
DOI :
10.1109/ISCAS.2001.921316