Search results

1 – 4 of 4
Content available
Article
Publication date: 3 August 2020

Mostafa Abd-El-Barr, Kalim Qureshi and Bambang Sarif

Ant Colony Optimization and Particle Swarm Optimization represent two widely used Swarm Intelligence (SI) optimization techniques. Information processing using…

Abstract

Ant Colony Optimization and Particle Swarm Optimization represent two widely used Swarm Intelligence (SI) optimization techniques. Information processing using Multiple-Valued Logic (MVL) is carried out using more than two discrete logic levels. In this paper, we compare two the SI-based algorithms in synthesizing MVL functions. A benchmark consisting of 50,000 randomly generated 2-variable 4-valued functions is used for assessing the performance of the algorithms using the benchmark. Simulation results show that the PSO outperforms the ACO technique in terms of the average number of product terms (PTs) needed. We also compare the results obtained using both ACO-MVL and PSO-MVL with those obtained using Espresso-MV logic minimizer. It is shown that on average, both of the SI-based techniques produced better results compared to those produced by Espresso-MV. We show that the SI-based techniques outperform the conventional direct-cover (DC) techniques in terms of the average number of product terms required.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

To view the access options for this content please click here
Article
Publication date: 5 June 2017

Elena Zaitseva and Vitaly Levashenko

The purpose of this paper is to develop a new mathematical method for the reliability analysis and evaluation of multi-state system (MSS) reliability that agrees with…

Abstract

Purpose

The purpose of this paper is to develop a new mathematical method for the reliability analysis and evaluation of multi-state system (MSS) reliability that agrees with specifics of such system. It is possible based on the application of multiple-valued logic (MVL) that is a natural extension of Boolean algebra used in reliability analysis.

Design/methodology/approach

Similar to Boolean algebra, MVL is used for the constriction of the structure function of the investigated system. The interpretation of the structure function of the MSS in terms of MVL allows using mathematical methods and approaches of this logic for the analysis of the structure function.

Findings

The logical differential calculus is one of mathematical approaches in MVL. The authors develop new method for MSS reliability analysis based on logical differential calculus, in particular direct partial logical derivatives, for the investigation of critical system states (CSSs). The proposed method allows providing the qualitative and quantitative analyses of MSS: the CSS can be defined for all possible changes of any system component or group of components, and probabilities of this state can also be calculated.

Originality/value

The proposed method permits representing the MSS in the form of a structure function that is interpreted as MVL function and provides the system analyses without special transformation into Boolean interpretation and with acceptable computational complexity.

Details

International Journal of Quality & Reliability Management, vol. 34 no. 6
Type: Research Article
ISSN: 0265-671X

Keywords

To view the access options for this content please click here
Article
Publication date: 11 November 2013

Alessio Monti, Luca Scorrano, Simone Tricarico, Filiberto Bilotti, Alessandro Toscano and Lucio Vegni

The purpose of this paper is to show how metamaterials with extreme values of permittivity and permeability, may be effectively used to design artificial magnetic…

Abstract

Purpose

The purpose of this paper is to show how metamaterials with extreme values of permittivity and permeability, may be effectively used to design artificial magnetic conductors (AMC) at a given frequency. In particular, this paper theoretically determines, for the different polarizations of the incidence field, the conditions under which metamaterials can behave as an AMC.

Design/methodology/approach

In order to find out the required values of the constitutive parameters, this paper has done a theoretical analysis based on the transmission-line theory. The obtained analytical reflection coefficient has been particularized for the different possible polarizations of the incidence field in order to find the constitutive parameters values that this paper needs for the AMC behavior.

Findings

Depending on the polarization of the field, it is shown that different values of the constitutive parameters are needed to get AMCs. In particular, it is shown that in the case of TEM and TE polarizations, a large value of the permeability is enough to obtain an AMC boundary condition. In the case of the TM polarization, instead, the AMC boundary condition is effectively achieved by using a material with vanishing permittivity. The role of the permittivity in the three polarizations is discussed. Finally, possible implementations and applications at microwave and optical frequencies are presented.

Originality/value

The idea of using miniaturized inclusions to obtain AMCs is not completely new. However, to the authors' best knowledge, a complete and rigorous theoretical analysis showing the capabilities and the limits of this approach has not yet been presented in the open technical literature.

Details

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 32 no. 6
Type: Research Article
ISSN: 0332-1649

Keywords

To view the access options for this content please click here
Article
Publication date: 5 June 2009

Anas N. Al‐Rabadi

New approaches for non‐classical neural‐based computing are introduced. The developed approaches utilize new concepts in three‐dimensionality, invertibility and…

Abstract

Purpose

New approaches for non‐classical neural‐based computing are introduced. The developed approaches utilize new concepts in three‐dimensionality, invertibility and reversibility to perform the required neural computing. The various implementations of the new neural circuits using the introduced paradigms and architectures are presented, several applications are shown, and the extension for the utilization in neural‐systolic computing is also introduced.

Design/methodology/approach

The new neural paradigms utilize new findings in computational intelligence and advanced logic synthesis to perform the functionality of the basic neural network (NN). This includes the techniques of three‐dimensionality, invertibility and reversibility. The extension of implementation to neural‐systolic computing using the introduced reversible neural‐systolic architecture is also presented.

Findings

Novel NN paradigms are introduced in this paper. New 3D paradigm of NL circuits called three‐dimensional inverted neural logic (3DINL) circuits is introduced. The new 3D architecture inverts the inputs and weights in the standard neural architecture: inputs become bases on internal interconnects, and weights become leaves of the network. New reversible neural network (RevNN) architecture is also introduced, and a RevNN paradigm using supervised learning is presented. The applications of RevNN to multiple‐output feedforward discrete plant control and to reversible neural‐systolic computing are also shown. Reversible neural paradigm that includes reversible neural architecture utilizing the extended mapping technique with an application to the reversible solution of the maze problem using the reversible counterpropagation NN is introduced, and new neural paradigm of reversibility in both architecture and training using reversibility in independent component analysis is also presented.

Originality/value

Since the new 3D NNs can be useful as a possible optimal design choice for compacting a learning (trainable) circuit in 3D space, and because reversibility is essential in the minimal‐power computing as the reduction of power consumption is a main requirement for the circuit synthesis of several emerging technologies, the introduced methods for non‐classical neural computation are new and interesting for the design of several future technologies that require optimal design specifications such as three‐dimensionality, regularity, super‐high speed, minimum power consumption and minimum size such as in low‐power control, adiabatic signal processing, quantum computing, and nanotechnology.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 2 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

1 – 4 of 4