Adaline Network
Adaline is an acronym for an adaptive linear element or adaptive linear neurone. It was developed by Bernard Widrow and Ted Hoff in 1960. It is a single layer neural network with multiple inputs and single outputs. Following are the variables used: x= input, wi = weight, n = number of neurons, θ = constant.
Summary
Adaline is an acronym for an adaptive linear element or adaptive linear neurone. It was developed by Bernard Widrow and Ted Hoff in 1960. It is a single layer neural network with multiple inputs and single outputs. Following are the variables used: x= input, wi = weight, n = number of neurons, θ = constant.
Things to Remember
- Adaline is an acronym for an adaptive linear element or adaptive linear neurone. It was developed by Bernard Widrow and Ted Hoff in 1960.
- It is a single layer neural network with multiple inputs and single outputs.
- Following are the variables used: x= input, wi = weight, n = number of neurons, θ = constant.
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Adaline Network
Adaline network
Adaline is an acronym for an adaptive linear element or adaptive linear neurone. It was developed by Bernard Widrow and Ted Hoff in 1960. It is a single layer neural network with multiple inputs and single outputs. The output provided by this neural network is given by,
where,
x= input,
wi = weight,
n = number of neurons
θ = constant.
References:
- Elaine Rich, Kevin Knight 1991, "Artificial Intelligence".
- Nilsson, Nils J. Principles of Artificial Intelligence, Narosa Publishing House New Delhi, 1998.
- Norvig, Peter & Russel, Stuart Artificial Intelligence: A modern Approach, Prentice Hall, NJ, 1995
- Patterson, Dan W. Introduction to Artificial Intelligence and Expert Systems, Prentice Hall of India Private Limited New Delhi, 1998.
Lesson
Applications of AI
Subject
Computer Engineering
Grade
Engineering
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