Analog implementation of pulse-coupled neural networks

Abstract

Abstract-This paper presents a compact architecture for analog CMOS hardware implementation of voltage-mode pulsecoupled neural networks (PCNN's). The hardware implementation methods shows inherent fault tolerance specialties and high speed, which is usually more than an order of magnitude over the software counterpart. A computational style described in this article mimics a biological neural network using pulse-stream signaling and analog summation and multiplication. Pulse-stream encoding technique uses pulse streams to carry information and control analog circuitry, while storing further analog information on the time axis. The main feature of the proposed neuron circuit is that the structure is compact, yet exhibiting all the basic properties of natural biological neurons. Functional and structural forms of neural and synaptic functions are presented along with simulation results. Finally, the proposed design is applied to image processing to demonstrate successful restoration of images and their features.

Review of pulse-coupled neural networks

“…Their architecture realizes weighting and summing signals in the PCNN [125]. Clark et al apply the PCNN into the optic system and build a novel adaptive optic system, which can reduce the noise propagation effects via smoothing technique of the PCNN [126].…”

CMOS architecture of synchronous pulse-coupled neural network and its application to image processing

“…Eckhom dynamic model represents a visual neuron as a multi-input element with a single output A leaky integrate-tD-fire pulse generatDr [8], unlike the medulatory EckhDm linking field, shDws that its nDise smoething capability is sperior �to median filtering and average-filter smDDthing. MDst dynamic models Df the neural CDmputatiDn suggest that synchronization between regions is the primary infDrmationcarr ier [8].…”

“…1 functions as follows. The circuit has two capacitors, C1 and C2• The stored charge on capacitor C I corresponds to the charge of sodium ions (Na+) accumulated on the external side of the biological neuron membrane, and the charge stored on Cz corresponds to the potassium ions (K+) accumulated inside the neuron cell [8]. The potential due to sodium ions changes at a faster rate than the potential due to potassium ions.…”

“…1 is an electronic at1alogy of a biological soma; i.e., it initiates reactions, with a given external stimulus, by genemting a stream of electrical pulse waves. In this case, the external stimulus is curre nt The circuit structure is based on the curr ent-driven simple neuron cells [5]- [7] and its voltage-driven circuit [8].…”

“…The idea of the neuristor is to abstract the five key axon properties of (i) threshold of excitation, (ii) refractory period, (iii) constant pulse-propagation velocity, (iv) pulse-shaping action during its propagation through the neuristor line, and (v) annihi lation of pulses in case of their collision. Pulse-stream encoding technique [4]- [8] uses pulse streams to carr y information and control analog circuitry, while storing further analog information on the time axis. The firing mte of action potentials in biological neurons is roughly proportional to change in the original gmded potential, which is categorized asfrequency modulation.…”