neural networ 1 (神经网络自学的英文材料)neural network 1 (神经网络自学的英文材料)neural network 1 (神经网络自学的英文材料)neural network 1 (神经网络自学的英文材料).ppt

Course Objectives What Will Not Be Covered Review of all architectures and learning rules Implementation VLSI Optical Parallel Computers Biology Psychology Historical Sketch Pre-1940: von Hemholtz, Mach, Pavlov, etc. General theories of learning, vision, conditioning No specific mathematical models of neuron operation 1940s: Hebb, McCulloch and Pitts Mechanism for learning in biological neurons Neural-like networks can compute any arithmetic function 1950s: Rosenblatt, Widrow and Hoff First practical networks and learning rules 1960s: Minsky and Papert Demonstrated limitations of existing neural networks, new learning algorithms are not forthcoming, some research suspended 1970s: Amari, Anderson, Fukushima, Grossberg, Kohonen Progress continues, although at a slower pace 1980s: Grossberg, Hopfield, Kohonen, Rumelhart, etc. Important new developments cause a resurgence in the field Applications Aerospace High performance aircraft autopilots, flight path simulations, aircraft control systems, autopilot enhancements, aircraft component simulations, aircraft component fault detectors Automotive Automobile automatic guidance systems, warranty activity analyzers Banking Check and other document readers, credit application evaluators Defense Weapon steering, target tracking, object discrimination, facial recognition, new kinds of sensors, sonar, radar and image signal processing including data compression, feature extraction and noise suppression, signal/image identification Electronics Code sequence prediction, integrated circuit chip layout, process control, chip failure analysis, machine vision, voice synthesis, nonlinear modeling Applications Financial Real estate appraisal, loan advisor, mortgage screening, corporate bond rating, credit line use analysis, portfolio trading program, corporate financial analysis, currency price prediction Manufacturing Manufacturing process control, product design and analysis, process and machine diagnosis, real-time particle identific