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This book constitutes the refereed proceedings of the 12th International Conference on Field-Programmable Logic and Applications, FPL 2002, held in Montpellier, France, in September 2002. The 104 revised regular papers and 27 poster papers presented together with three invited contributions were carefully reviewed and selected from 214 submissions. The papers are organized in topical sections on rapid prototyping, FPGA synthesis, custom computing engines, DSP applications, reconfigurable fabrics, dynamic reconfiguration, routing and placement, power estimation, synthesis issues, communication applications, new technologies, reconfigurable architectures, multimedia applications, FPGA-based arithmetic, reconfigurable processors, testing and fault-tolerance, crypto applications, multitasking, compilation techniques, etc.
Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly in unpredictable environments through mechanisms of adaptation and learning. This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation. As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.
Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networ...
2004 marks the 100th anniversary of the first description of the autoimmune disease paroxysmal cold hemoglobinuria, a rare hemolytic disorder, by Julius Donath and Karl Landsteiner. After a century of research, the list of autoimmune diseases has become impressive. With a prevalence of approximately 5% of the world-wide population, these chronic, debilitating conditions affect almost every major organ of the body and, for reasons that remain unclear, are much more prevalent in woman than in men. Despite our rapidly expanding knowledge of the cellular and molecular pathways that govern a normal immune response, deciphering the precise etiology of autoimmune diseases remains an important chall...
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NETosis is a unique form of cell death that is characterized by the release of decondensed chromatin and granular contents to the extracellular space. The initial observation of NETosis placed the process within the context of the innate immune response to infections. Neutrophils, the most numerous leukocytes that arrive quickly at the site of an infection, were the first cell type shown to undergo extracellular trap formation. However, subsequent studies showed that other granulocytes are also capable of releasing nuclear chromatin following stimulation. The extracellular chromatin acts to immobilize microbes and prevent their dispersal in the host. Bacterial breakdown products and inflamma...