Mohammed Ismail

TL;DR: A Neural Processor for Maze Solving and Issues in Analog VLSI and MOS Techniques for Neural Computing are discussed.

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).

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.

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.

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.