1. الرئيسية
  2. Thesis

Thesis

Genetic based clustering for image segmentation and vector quantization.

The purpose of this research is to see how useful it to use genetic programming in performing image clustering as well as in performing vector quantization for image compression applications. Two genetic based clustering algorithms (Centroid Based Genetic Clustering Algorithm CBGCA and Partition Based Genetic Clustering Algorithm CBGCA) implemented for clustering a two-dimensional gray level images. Also, the traditional K-means clustering algorithm implemented, which used for comparison purpose.

إنجليزية

Genetic learning of neural networks

A neural network has a parallel-distributed architecture with a large number of nodes and connection weights. The learning rule is one of the important attributes to specify for a neural network. It determines how to adapt connection weights in order to optimize the network performance. The Backpropagation network is the most well known and widely used among the current types of neural network systems available. It is a multilayer feedforward network with a powerful learning rule. The learning rule is known as Backpropagation.

إنجليزية

Recognition of some isolated spoken dos commands using neural networks.

The main objective of this work is to' implement a simple isolated_word speech recognition system. The system compares a spoken word with the templates that have been created; if it finds a match, ft 'recognizes' the word, and the computer does whatever it has been set up to do when that word is recognized; i.e., the system will execute the DOS command which corresponds to the input speech signal. The vocabulary consists of 11 isolated words, which form some of the DOS commands, recorded for one male speaker.

إنجليزية
المزيد