Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Analog-to-Digital Conversion Using Single-Layer Integrate-and-Fire Networks with Inhibitory Connections | EURASIP Journal on Applied Signal Processing 2004 13 2066-2075 2004 Hindawi Publishing Corporation Analog-to-Digital Conversion Using Single-Layer Integrate-and-Fire Networks with Inhibitory Connections Brian C. Watson Department of Electrical and Computer Engineering University of California San Diego La Jolla CA 92093 USA Email bc7watson@ Barry L. Shoop Department of Electrical Engineering and Computer Science Photonics Research Center United States Military Academy West Point NY 10996 USA Email barry-shoop@ Eugene K. Ressler Department of Electrical Engineering and Computer Science Photonics Research Center United States Military Academy West Point NY 10996 USA Email de8827@ Pankaj K. Das Department of Electrical and Computer Engineering University of California San Diego La Jolla CA 92093 USA Email das@ Received 14 December 2003 Revised 6 April 2004 Recommended for Publication by Peter Handel We discuss a method for increasing the effective sampling rate of binary A D converters using an architecture that is inspired by biological neural networks. As in biological systems many relatively simple components can act in concert without a predetermined progression of states or even a timing signal clock . The charge-fire cycles of individual A D converters are coordinated using feedback in a manner that suppresses noise in the signal baseband of the power spectrum of output spikes. We have demonstrated that these networks self-organize and that by utilizing the emergent properties of such networks it is possible to leverage many A D converters to increase the overall network sampling rate. We present experimental and simulation results for networks of oversampling 1-bit A D converters arranged in single-layer integrate-and-fire networks with inhibitory connections. In addition we demonstrate information transmission and preservation through chains of cascaded single-layer networks. Keywords and phrases spiking neurons .