Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/9345
Title: NEURAL NETWORKS ANALYSIS AND COMPUTATION
Authors: Lekhi, Lt. Vinay Kumar
Keywords: ELECTRONICS AND COMPUTER ENGINEERING;NEURAL NETWORKS ANALYSIS;NEURAL NETWORK;DIGITAL COMPUTER
Issue Date: 1995
Abstract: It is a known fact that the human brain is superior to a digital computer at many tasks. A good example of this is the processing of visual information; a one-year old baby is much faster and better at recognizing objects, faces etc. than even the most advanced Al system running on the fastest super computer. The brain has many significantly superior features that would be desirable to be incorporated in an artificial system [36] :- 1. It should be robust and fault tolerant. Nerve- cells in the brain die every day without affecting its performance. 2. It should be flexible, it can easily adjust to new environment by "Learning". 3. It should be able to deal with information that is fuzzy, probabilistic, noisy or inconsistent. 4. It should be highly parallel. 5. It should be small, compact and dissipate very little power. These features give us our real motivation to study a neuron and neural networks. Neural networks are emerging computational technology which 1 can significantly enhance a number of applications. They can be developed within a reasonable time frame and can often perform tasks better than other, more conventional technologies. When embedded in a hardware implementation neural networks exhibits a high degree of fault tolerance to system damage, they also offer high overall data throughput rates due to parallel data processing.....
URI: http://hdl.handle.net/123456789/9345
Other Identifiers: M.Tech
Research Supervisor/ Guide: Kumar, Vijay
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' DISSERTATIONS (E & C)

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