Unipolar terminal-attractor-based neural associative memory with adaptive threshold and perfect convergence

A perfectly convergent unipolar neural associative-memory system based on nonlinear dynamical terminal attractors is presented. With adaptive setting of the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal attractors, perfect convergence is achieved. This achievement and correct retrieval are demonstrated by computer simulation. The simulations are completed (1) by exhaustive tests with all of the possible combinations of stored and test vectors in small-scale networks and (2) by Monte Carlo simulations with randomly generated stored and test vectors in large-scale networks with an M/N ratio of 4 (M is the number of stored vectors; N is the number of neurons < 256). An experiment with exclusive-oR logic operations with liquid-crystal-television spatial light modulators is used to show the feasibility of an optoelectronic implementation of the model. The behavior of terminal attractors in basins of energy space is illustrated by examples

Techniques for video compression

In this report, we present our study on multiprocessor implementation of a MPEG2 encoding algorithm. First, we compare two approaches to implementing video standards, VLSI technology and multiprocessor processing, in terms of design complexity, applications, and cost. Then we evaluate the functional modules of MPEG2 encoding process in terms of their computation time. Two crucial modules are identified based on this evaluation. Then we present our experimental study on the multiprocessor implementation of the two crucial modules. Data partitioning is used for job assignment. Experimental results show that high speedup ratio and good scalability can be achieved by using this kind of job assignment strategy

Unipolar terminal-attractor based neural associative memory with adaptive threshold

A unipolar terminal-attractor based neural associative memory (TABAM) system with adaptive threshold for perfect convergence is presented. By adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors for the purpose of reducing the spurious states in a Hopfield neural network for associative memory and using the inner product approach, perfect convergence and correct retrieval is achieved. Simulation is completed with a small number of stored states (M) and a small number of neurons (N) but a large M/N ratio. An experiment with optical exclusive-OR logic operation using LCTV SLMs shows the feasibility of optoelectronic implementation of the models. A complete inner-product TABAM is implemented using a PC for calculation of adaptive threshold values to achieve a unipolar TABAM (UIT) in the case where there is no crosstalk, and a crosstalk model (CRIT) in the case where crosstalk corrupts the desired state

A New Forward Secure Signature Scheme using Bilinear Maps

Forward-secure signatures are used to defeat signature forgeries in cases of key exposure. In this model, the signature key evolves with time and it is computationally infeasible for an adversary to forge a signature for some time-period prior to the key’s exposure. In this paper a new forward-secure digital signature scheme is presented, which is based on the use of bilinear maps recently advocated by Boneh and Franklin [9]. This scheme is efficiently constructed and can be used with a large number of time periods with a log magnitude complexity. The signing and key-update operations are very efficient when compared with other previously available schemes. A formal definition, as well as a detailed analysis of the security performance or this scheme, is presented. The security proof for this scheme is based on the Computational Diffie-Hellman assumption, which leads to a unique approach to proving security in the random oracle model. Furthermore, within the proof both the hash oracle and the signing oracle are constructed in an innovative manner

Basic engineering circuit analysis

Indeks *** *** Bibliografi hlm. Setiap babxiii, 976 hlm. : il. ; 24 cm

Emerging multimedia computer comunication technologys

xx.443 : 24 c

Introduction to computer networks and cybersecurity

xlv, 1336 p.; 28.5 c

Emerging multimedia computer communication technologies

Indeks Bibliografi hlm. Setiap babxvii, 443 hlm. :il. ;24 cm

1.1 The Key Exposure Problem

Forward-secure signatures are used to defeat signature forgeries in cases of key exposure. In this model, the signature key evolves with time and it is computationally infeasible for an adversary to forge a signature for some timeperiod prior to the key’s exposure. In this paper a new forward-secure digital signature scheme is presented, which is based on the use of bilinear maps recently advocated by Boneh and Franklin [9]. This scheme is efficiently constructed and can be used with a large number of time periods with a log magnitude complexity. The signing and key-update operations are very efficient when compared with other previously available schemes. A formal definition, as well as a detailed analysis of the security performance or this scheme, is presented. The security proof for this scheme is based on the Computational Diffie-Hellman assumption, which leads to a unique approach to proving security in the random oracle model. Furthermore, within the proof both the hash oracle and the signing oracle are constructed in an innovative manner