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Yves Blaquiere

Researcher at École de technologie supérieure

Publications -  82
Citations -  427

Yves Blaquiere is an academic researcher from École de technologie supérieure. The author has contributed to research in topics: Field-programmable gate array & Integrated circuit. The author has an hindex of 9, co-authored 78 publications receiving 390 citations. Previous affiliations of Yves Blaquiere include Université du Québec à Montréal & École Polytechnique de Montréal.

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Patent

Methods, apparatus and system to support large-scale micro- systems including embedded and distributed power supply, thermal regulation, multi-distributed-sensors and electrical signal propagation

TL;DR: In this paper, the authors present technologies for integrated circuits and large area integrated circuits (LAICs), which are integrated circuits made from photo-repetition of one or several reticle image fields, stitched together on at least one lithographic process layer.
Proceedings ArticleDOI

An active reconfigurable circuit board

TL;DR: Preliminary results are promising, confirming that this smart reconfigurable circuit board can be implemented using a wafer-scale approach in a mature and low-cost 6-metal layer CMOS 0.18 mum technology.
Patent

Methods, apparatus, and systems for reducing interference on nearby conductors

TL;DR: In this paper, a method of data transmission according to one embodiment of the invention, data transitions on adjacent conductors are separated in time, where signals on the adjacent conductive paths pass through different alternating sequences of inversions and regenerations.
Proceedings ArticleDOI

An interconnection network for a novel reconfigurable circuit board

TL;DR: Implementation results show the feasibility of this proposed cell-based array network that could interconnect a very large number of nodes, spread over an area that could fill a whole wafer, using a typical 6-metal 0.18 mum CMOS technology.
Proceedings ArticleDOI

A VLSI architecture for fast clustering with fuzzy ART neural networks

TL;DR: The fuzzy ART network's algorithm is reformulated, and then a novel fuzzy ART system architecture is proposed, composed of a global comparator and several identical elementary modules (EMs), each one emulating a number of neurons.