Supervised Learning Concept with MCQs

Elements of ANN,its type & application areas

Processing Elements of Artificial Neural Network

A processing unit is made up of summing unit followed by an output unit. The function of a summing unit is to take n input values, weight each input value and calculate the weighted sum of those values.

Based on the sign of the weight of each input, it is determined whether the input has a positive weight or a negative weight.

The weighted sum of the summing unit is known as Activation Value and based on the signal from this activation value, the output is produced.

Both the input and output can be either continuous or discrete as well as they can be either deterministic or fuzzy.

Positive weight – excitatory input

Negative weight – inhibitory input

Two important areas where ANNs have a huge potential of applications are Speech and Image Processing

Applications in Speech Recognition

1.Vowel Classification

2.Recognition of vowel-consonant segments

3.Recognition of stop consonant-vowel utterances in Indian languages

4.Nettalk

5.Phonetic Typewriter

Applications in Image Processing

1.Recognition of Symbols (used in Olympics)

2.Recognition of handwriting

3.Segmentation of image

4.Classification and segmentation of texture