0301-662 - Neural Networks

Institution:

Rochester Institute of Technology

Subject:

Description:

Artificial Neural Networks (ANN) is the name given to a broad class of processing algorithms that are loosely based on how the brain processes information. The term "artificial" distinguishes the silicon-based systemsfrom the biological systems (such as ourselves). ANNs are used in numerous applications from manufacturing controls to handwriting recognition to optical visual processing, or in any application that can handle some "fuzziness"in the output. ANNs also form the foundation for artifi cial intelligence (AI) systems. This course begins with a discussion of what ANNs are and what features defi ne them, then examines a number of the most common neural algorithms and techniques such as backward error propagation ("Back-prop").Software implementations of the algorithms (requiring C programming skills) as well as hardware implementations (requiring PSPICE simulations) will be discussed. Class 4, Credit 4

Credits:

4.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.rit.edu/

Phone Number:

(585) 475-2411

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Quarter

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