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This paper reviews challenges and progress in implementing timing-based neuronal learning mechanisms in silicon. ABSTRACT | The ability to carry out signal processing, classification, recognition, and computation in artificial spiking neural networks (SNNs) is mediated by their synap-ses. In particular, through activity-dependent alteration of their(More)
The main result of this paper is the development of a low depth carry lookahead addition technique based on threshold logic. Two such adders are designed using the recently proposed charge recycling threshold logic gate. The adders are shown to have a very low logic depth, and significantly reduced area and power dissipation compared to other dynamic CMOS(More)
Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN)(More)
Physical unclonable functions (PUFs) exploit the intrinsic complexity and irreproducibility of physical systems to generate secret information. The advantage is that PUFs have the potential to provide fundamentally higher security than traditional cryptographic methods by preventing the cloning of devices and the extraction of secret keys. Most PUF designs(More)
—Spike-Timing Dependent Plasticity (STDP) is believed to play an important role in learning and the formation of computational function in the brain. The classical model of STDP which considers the timing between pairs of pre-synaptic and post-synaptic spikes (p-STDP) is incapable of reproducing synaptic weight changes similar to those seen in biological(More)
—As conventional memory technologies are challenged by their technological physical limits, emerging technologies driven by novel materials are becoming an attractive option for future memory ar-chitectures. Among these technologies, Resistive Memories (ReRAM) created new possibilities because of their nano-features and unique I-V characteristics. One(More)
Triplet-based Spike Timing Dependent Plasticity (TSTDP) is a powerful synaptic plasticity rule that acts beyond conventional pair-based STDP (PSTDP). Here, the TSTDP is capable of reproducing the outcomes from a variety of biological experiments, while the PSTDP rule fails to reproduce them. Additionally, it has been shown that the behaviour inherent to the(More)
—The Bienenstock-Cooper-Munro (BCM) and Spike Timing-Dependent Plasticity (STDP) rules are two experimentally verified form of synaptic plasticity where the alteration of synap-tic weight depends upon the rate and the timing of pre-and post-synaptic firing of action potentials, respectively. Previous studies have reported that under specific conditions,(More)
This paper presents SPICE ready circuit models that system designers can use to accurately measure the behavior of memristor-based large systems. ABSTRACT | The nonvolatile memory property of a memristor enables the realization of new methods for a variety of computational engines ranging from innovative memristive-based neuromorphic circuitry through to(More)
This paper presents the design exploration of CMOS 64-bit adders designed using threshold logic gates based on systematic transistor level delay estimation using Logical Effort (LE). The adders are hybrid designs consisting of domino and the recently proposed Charge Recycling Threshold Logic (CRTL). The delay evaluation is based LE modeling of the delay of(More)