Solving sylvester matrix equations with LR bipolar triangular fuzzy numbers in electric circuits problems

Bipolar crisp numbers refer to two different functions and information in a given system, namely positive and negative components. Likelihood and unlikelihood information can be simultaneously represented by bipolar crisp numbers rather than classical crisp numbers. However, since bipolar crisp numbers are inadequate in dealing with uncertainty problem, bipolar fuzzy numbers (BFN) are used instead. BFN in Sylvester matrix equations (SME) plays an essential role in the control system such as in electrical controller. An electrical controller of RLC circuit consisting of resistor (R), inductor (L), and capacitor (C), is used to control the amount of electric currents flowing across the electric circuits. Besides, complex numbers which consist of real and imaginary parts are used in solving RLC circuit, where real numbers denote resistance, while imaginary numbers denote inductance or capacitance. To the best of our knowledge, the integration of SME with either BFN or complex BFN is not yet explored. Therefore, this study aims to construct analytical approaches in solving bipolar fuzzy Sylvester matrix equation (FSME), complex bipolar FSME, bipolar fully fuzzy Sylvester matrix equation (FFSME), and complex bipolar fully fuzzy linear system (FFLS) in left-right (LR) bipolar triangular fuzzy numbers. In order to obtain the solutions, bipolar FSME, complex bipolar FSME, and bipolar FFSME are converted into the bipolar linear system by utilizing Kronecker product and Vecoperator. Next, an equivalent bipolar linear system (EBLS), equivalent complex bipolar linear system (ECBLS), associated bipolar linear system (ABLS), and associated complex bipolar linear system (ACBLS) are established. Then, the final solutions of the constructed methods are obtained using inverse method. Therefore, four analytical approaches have been constructed in solving bipolar FSME, complex bipolar FSME, bipolar FFSME, and complex bipolar FFLS in LR forms. Several examples are presented to illustrate the constructed methods. Moreover, the application of RLC circuits with complex bipolar FSME and complex bipolar FFLS are also carried out. In conclusion, the new findings of analytical approaches add to the fuzzy equations body of knowledge with significant applications in bipolar electrical controllers

Properties of Bipolar Fuzzy Hypergraphs

In this article, we apply the concept of bipolar fuzzy sets to hypergraphs and investigate some properties of bipolar fuzzy hypergraphs. We introduce the notion of $A-$ tempered bipolar fuzzy hypergraphs and present some of their properties. We also present application examples of bipolar fuzzy hypergraphs

A modular CMOS analog fuzzy controller

The low/medium precision required for many fuzzy applications makes analog circuits natural candidates to design fuzzy chips with optimum speed/power figures. This paper presents a sixteen rules-two inputs analog fuzzy controller in a CMOS 1 /spl mu/m single-poly technology based on building blocks implementations previously proposed by the authors (1995). However, such building blocks are rearranged here to get a highly modular architecture organized from two high level blocks: the label block and the rule block. In addition, sharing of membership function circuits allows a compact design with low area and power consumption and its highly modular architecture will permit to increase the number of inputs and rules in future chips with hardly design effort. The paper includes measurements from a silicon prototype of the controller

Using Building Blocks to Design Analog Neuro-Fuzzy Controllers

We present a parallel architecture for fuzzy controllers and a methodology for their realization as analog CMOS chips for low- and medium-precision applications. These chips can be made to learn through the adaptation of electrically controllable parameters guided by a dedicated hardware-compatible learning algorithm. Our designs emphasize simplicity at the circuit level—a prerequisite for increasing processor complexity and operation speed. Examples include a three-input, four-rule controller chip in 1.5-μm CMOS, single-poly, double-metal technology

CMOS current-mode chaotic neurons

This paper presents two nonlinear CMOS current-mode circuits that implement neuron soma equations for chaotic neural networks, and another circuit to realize programmable current-mode synapse using CMOS-compatible BJT's. They have been fabricated in a double-metal, single-poly 1.6 /spl mu/m CMOS technology and their measured performance reached the expected function and specifications. The neuron soma circuits use a novel, highly accurate CMOS circuit strategy to realize piecewise-linear characteristics in the current-mode domain. Their prototypes obtain reduced area and low voltage power supply (down to 3 V) with clock frequency of 500 kHz. As regard to the synapse circuit, it obtains large linearity and continuous, linear, weight adjustment by exploration of the exponential-law operation of CMOS-BJT's. The full accordance observed between theory and measurements supports the development of future analog VLSI chaotic neural networks to emulate biological systems and advanced computation

Automatic programming methodologies for electronic hardware fault monitoring

This paper presents three variants of Genetic Programming (GP) approaches for intelligent online performance monitoring of electronic circuits and systems. Reliability modeling of electronic circuits can be best performed by the Stressor - susceptibility interaction model. A circuit or a system is considered to be failed once the stressor has exceeded the susceptibility limits. For on-line prediction, validated stressor vectors may be obtained by direct measurements or sensors, which after pre-processing and standardization are fed into the GP models. Empirical results are compared with artificial neural networks trained using backpropagation algorithm and classification and regression trees. The performance of the proposed method is evaluated by comparing the experiment results with the actual failure model values. The developed model reveals that GP could play an important role for future fault monitoring systems.This research was supported by the International Joint Research Grant of the IITA (Institute of Information Technology Assessment) foreign professor invitation program of the MIC (Ministry of Information and Communication), Korea

Measurements, Models, Systems and Design

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