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Motivated by advantages of current-mode design, this brief contribution explores the implementation of weight matrices in neuromemristive systems via current-mode memristor crossbar circuits. After deriving theoretical results for the range…

Machine Learning · Statistics 2017-07-19 Cory Merkel

A general fuzzy min-max (GFMM) neural network is one of the efficient neuro-fuzzy systems for classification problems. However, a disadvantage of most of the current learning algorithms for GFMM is that they can handle effectively numerical…

Machine Learning · Computer Science 2020-09-02 Thanh Tung Khuat , Bogdan Gabrys

In this paper, we present a generalization of the relational data model based on paraconsistent intuitionistic fuzzy sets. Our data model is capable of manipulating incomplete as well as inconsistent information. Fuzzy relation or…

Databases · Computer Science 2007-05-23 Rajshekhar Sunderraman , Haibin Wang

A quantum memristor is a resistive passive circuit element with memory engineered in a given quantum platform. It can be represented by a quantum system coupled to a dissipative environment, in which a system-bath coupling is mediated…

Quantum Physics · Physics 2020-02-18 Tasio Gonzalez-Raya , Joseph M. Lukens , Lucas C. Céleri , Mikel Sanz

The memristor, the recently discovered fundamental circuit element, is of great interest for neuromorphic computing, nonlinear electronics and computer memory. It is usually modelled either using Chua's equations, which lack material device…

Materials Science · Physics 2014-04-23 Ella Gale

Due to many limitations of Von Neumann architecture such as speed, memory bandwidth, efficiency of global interconnects and increase in the application of artificial neural network, researchers have been pushed to look into alternative…

Emerging Technologies · Computer Science 2019-05-15 Harshit Roy , Mrigank Sharad

Memristor-based neuromorphic computing could overcome the limitations of traditional von Neumann computing architectures -- in which data are shuffled between separate memory and processing units -- and improve the performance of deep…

Numerous learning methods for fuzzy cognitive maps (FCMs), such as the Hebbian-based and the population-based learning methods, have been developed for modeling and simulating dynamic systems. However, these methods are faced with several…

Machine Learning · Computer Science 2019-08-23 Guoliang Feng , Wei Lu , Witold Pedrycz , Jianhua Yang , Xiaodong Liu

Designing a robust controller for Modular Multilevel Converters (MMCs) is crucial to ensure stability and optimal dynamic performance under various operating conditions, including faulty and disturbed scenarios. The primary objective of…

Systems and Control · Electrical Eng. & Systems 2024-04-30 Mohammad Ali Labbaf-Khaniki , Mohammad Manthouri , Amin Hajizadeh

In this paper we show E-FuzzEdge, a novel fuzzing architecture targeted towards improving the throughput of fuzzing campaigns in contexts where scalability is unavailable. E-FuzzEdge addresses the inefficiencies of hardware-in-the-loop…

Cryptography and Security · Computer Science 2025-10-03 Davide Rusconi , Osama Yousef , Mirco Picca , Flavio Toffalini , Andrea Lanzi

This paper proposes a fuzzy goal programming based on Taylor series for solving decentralized bi-level multiobjective fractional programming (DBLMOFP) problem. In the proposed approach, all of the membership functions are associated with…

Optimization and Control · Mathematics 2016-06-06 Hasan Dalman

An investigation of deep fuzzy systems is presented in this paper. A deep fuzzy system is represented by recursive fuzzy systems from an input terminal to output terminal. Recursive fuzzy systems are sequences of fuzzy grade memberships…

Other Computer Science · Computer Science 2019-06-20 Khaled Ahmed Nagaty

Fuzzy logic controllers are readily customizable in natural language terms and can effectively deal with nonlinearities and uncertainties in control systems. This paper presents an intelligent and automated fuzzy control procedure for the…

Signal Processing · Electrical Eng. & Systems 2019-11-07 Issam Damaj , Jean Saade , Hala Al-Faisal , Hassan Diab

Matrix factorization (MF) discovers latent features from observations, which has shown great promises in the fields of collaborative filtering, data compression, feature extraction, word embedding, etc. While many problem-specific…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-08-14 Wei Tan , Shiyu Chang , Liana Fong , Cheng Li , Zijun Wang , Liangliang Cao

The thesis investigates the utilization of memristive and memcapacitive crossbar arrays in low-power machine learning accelerators, offering a comprehensive co-design framework for deep neural networks (DNN). The model, implemented through…

Neural and Evolutionary Computing · Computer Science 2024-03-06 Ankur Singh

Designing a mechatronic system is a complex task since it deals with a high number of system components with multi-disciplinary nature in the presence of interacting design objectives. Currently, the sequential design is widely used by…

Robotics · Computer Science 2020-08-25 Abolfazl Mohebbi , Sofiane Achiche , Luc Baron

Anyone who looks into the circuitry world will be familiar with the three fundamental circuit elements - capacitor, resistor, and inductor. These circuit elements are defined by the relation between two of the four fundamental circuit…

Emerging Technologies · Computer Science 2022-05-26 Manoj Mathews

Memristors are emerging as key electronic components that retain resistance states without power. Their non-volatile nature and ability to mimic synaptic behavior make them ideal for next-generation memory technologies and neuromorphic…

Mesoscale and Nanoscale Physics · Physics 2025-10-28 Tongxin Chen , Yinyu Nie , Yafei Hao , Shengchun Shen , Jiajun Pan , Xiaoguang Li , Yuan Lu

With the continuous advancement of processors, modern micro-architecture designs have become increasingly complex. The vast design space presents significant challenges for human designers, making design space exploration (DSE) algorithms a…

Machine Learning · Computer Science 2024-12-17 Hanwei Fan , Ya Wang , Sicheng Li , Tingyuan Liang , Wei Zhang

We propose a general method for constructing a fuzzy cellular automaton from a given cellular automaton. Unlike previous approaches that use fuzzy distinctive normal form, whose update function is restricted to third-order polynomials, our…

Cellular Automata and Lattice Gases · Physics 2026-01-26 Seiryu Shimizu , Tetsuji Tokihiro
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