M
Mohammed Ismail
Researcher at Wayne State University
Publications - 587
Citations - 8769
Mohammed Ismail is an academic researcher from Wayne State University. The author has contributed to research in topics: CMOS & Operational amplifier. The author has an hindex of 43, co-authored 557 publications receiving 7964 citations. Previous affiliations of Mohammed Ismail include Khalifa University & Ohio State University.
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Analog VLSI implementation of neural systems
Carver A. Mead,Mohammed Ismail +1 more
TL;DR: A Neural Processor for Maze Solving and Issues in Analog VLSI and MOS Techniques for Neural Computing are discussed.
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A comprehensive review of Thermoelectric Generators: Technologies and common applications
Nesrine Jaziri,Nesrine Jaziri,Nesrine Jaziri,Ayda Boughamoura,Jens Muller,Brahim Mezghani,Fares Tounsi,Mohammed Ismail +7 more
TL;DR: In-depth analysis of TEGs is presented, starting by an extensive description of their working principle, types, used materials, figure of merit, improvement techniques including different thermoelectric materials arrangement (conventional, segmented and cascaded), and used technologies and substrates types (silicon, ceramics and polymers).
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Statistical modeling of device mismatch for analog MOS integrated circuits
TL;DR: A generalized parameter-level statistical model, called statistical MOS (SMOS), capable of generating statistically significant model decks from intra- and inter-die parameter statistics is described, and Calculated model decks preserve the inherent correlations between model parameters while accounting for the dependence of parameter variance on device separation distance and device area.
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RF bandpass filter design based on CMOS active inductors
TL;DR: In this paper, a second-order RF bandpass filter based on active inductor has been implemented in a 0.35 /spl mu/m CMOS process, which has 28dB spurious-free-dynamic-range (SFDR) and total current consumption (including buffer stage) is 17 mA with 2.7-V power supply.
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Low-Power ECG-Based Processor for Predicting Ventricular Arrhythmia
Nourhan Bayasi,Temesghen Tekeste,Hani Saleh,Baker Mohammad,Ahsan H. Khandoker,Mohammed Ismail +5 more
TL;DR: This paper presents the design of a fully integrated electrocardiogram (ECG) signal processor (ESP) for the prediction of ventricular arrhythmia using a unique set of ECG features and a naive Bayes classifier.