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With a similar capability of processing spikes as biological neural systems, networks of spiking neurons are expected to achieve a performance similar to that of living brains. In recent days, many great achievements have been made in spiking neuron models and its learning algorithm. We build an integrated model using spiking neural networks (SNNs), which performs phase encoding method and delay learning-based...
Visual object tracking (VOT) is one of the most challenging problems in the field of computer vision, which plays a crucial role in many applications, especially in human-computer interaction, surveillance and robotics. This paper investigates the contribution of perceptual hash algorithm (PHA) in visual object tracking, which is to generate a “fingerprint” string for each image, and then compare...
Pulse-Coupled Neural Network is known as third generation artificial neural network. It is created by visual cortex neurons, a synchronous pulse release phenomenon of mammals. Compare to traditional artificial neural network, PCNN has the characteristics of dynamic neural network, integrated space-time, automatic propagation and synchronous pulse release. PCNN has tendency for image retention information...
In the distributed environments, Anonymous Access and Delegation are not satisfied in the traditional Access Control. However, they can be guaranteed in the Key-based Trust Models, because a key represents the identification of one user, both authorization and key are associated with each other. In the Key-based Trust Models, the most representative ones are PolicyMaker, SPKI/SDSI and QCM. In this...
In this paper, we extend the neural network based approaches, which can asymptotically compute the largest or smallest eigenvalues and the corresponding eigenvectors of real symmetric matrix, to the real antisymmetric matrix case. Given any n-by-n real antisymmetric matrix, unlike the previous neural network based methods that were summarized by some ordinary differential equations (ODEs) with 2n...
With the continuous expansion of the network size, some networks gradually present the characteristics of social networks, especially, scale-free networks. At present, some theoretical studies of scale-free networks are mainly based on simulated platforms. Based on this, the question that how we fast simulate a network model possessing scale-free effects and presenting related characteristics of realistic...
This paper presents the probabilistic logic model to compute the probability distribution of the nano gate states. The characterization is based on the Markov random field and statistic physics. The primary logic gates are probabilistically characterized. The effectiveness of the method is demonstrated by a full adder and an 8-bit adder. The analysis shows that the device probability distribution...
Device failure is an important consideration in nano-scale design. This paper presents a probabilistic logic model to compute the probability distribution of the nano gate states. The characterization is based on Markov random field and statistical physics. The basic logic gates are probabilistically characterized. The effectiveness of the method is demonstrated by an inverter and the inverter cascade...
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