The aim of the book is to design a simulation model of Brushless dc motor and to control its speed at different values of load torques.In this light, new control schemes should be devised for a better solution of a non linear system. Recently, work has been started toward the development of Artificial Neural Network (ANN) based intelligent controllers. The ANN has several key features that make it highly suitable for BLDCM speed applications. The ANN based PID controller is used for the speed control of BLDCM at different values of load torque and its comparison is done with the conventional controllers like PID and PI controllers.

Cross-correlation and related techniques have dominated the Image processing field since the early fifties. Conventional template matching algorithm based on cross-correlation requires complex calculation and large time for object detection, which makes difficult to use them in real time applications. The shortcomings of this class of image matching methods have caused a slow-down in the development of operational automated correlation systems. In the proposed book particle swarm optimization & its variants based algorithm is used for detection of object in image. Implementation of this algorithm reduces the time required for object detection than conventional template matching algorithm. Algorithm can detect object in less number of iteration & hence less time & energy than the complexity of conventional template matching. This feature makes the method capable for real time implementation.