Implementation of Back Propagation Neural Network with PCA for Face Recognition

Face recognition is truly one of the demanding fields of biometric image processing system Within this paper we have implemented Back Propagation Neural Network for face recognition using MATLAB where feature extraction and face identification system completely depend on Principal Component Analysis PCA Face images are multidimensional and variable data Hence we cannot directly apply Back Propagation Neural Network to classify face without extracting the core area of face So the dimensionality of face image is reduced by the Principal Component Analysis algorithm then we have to explore unique feature for all stored database images called eigenfaces of eigenvectors These unique features or eigenvectors are given as parallel input to the Back Propagation Neural Network BPNN for recognition of given test images Here test image is taken from the integrated webcam which is applied to the BPNN trained network The maximum output of the tested network gives the index of recognized face image BPNN employing PCA is more robust and reliable than PCA based face recognition syste

Implementation and Performance Analysis of Different Hand Gesture Recognition Methods

In recent few years, hand gesture recognition is one of the advanced grooming technologies in the era of human-computer interaction and computer vision due to a wide area of application in the real world. But it is a very complicated task to recognize hand gesture easily due to gesture orientation, light condition, complex background, translation and scaling of gesture images. To remove this limitation, several research works have developed which is successfully decrease this complexity. However, the intention of this paper is proposed and compared four different hand gesture recognition system and apply some optimization technique on it which ridiculously increased the existing model accuracy and model running time. After employed the optimization tricks, the adjusted gesture recognition model accuracy was 93.21% and the run time was 224 seconds which was 2.14% and 248 seconds faster than an existing similar hand gesture recognition model. The overall achievement of this paper could be applied for smart home control, camera control, robot control, medical system, natural talk, and many other fields in computer vision and human-computer interaction

Enhancing Transmission Capacity of a Cognitive Radio Network by Joint Spatial-Temporal Sensing with Cooperative Communication Strategy

In static cognitive radio network a secondary transmitter communicates directly with a secondary receiver only when the spectrum is not occupied by any primary user. The secondary user has to stop its transmission when no spectrum holes exist. To improve the transmission capacity, in this paper we approach to combine cognitive radio network with cooperative communication strategy employing spatial sensing as well as temporal sensing. In our proposed scheme when primary user is active, a secondary user transmits to another secondary user via a relay channel. By enabling the use of both the direct and relay channels, the transmission performance of the secondary system can be improved significantly. Our information-theoretic analysis as well as numerical results show that the proposed scheme significantly reduces the average symbol error probability compared to schemes based on pure temporal or spatial sensing

Performance Analysis of TCP Tahoe, Reno, New Reno, Sack and Vegas using NS-2

The Transmission Control Protocol TCP is the dominating end-to-end protocol on the internet today but still it faces congestion problems in some cases To overcome congestion problems several congestion control and avoiding mechanisms namely Tahoe Reno Vegas and Sack etc all with different features and advantages but with maximal throughput as main objective which are termed as the clones of TCP have been incorporated into TCP IP protocol for handling congestion efficiently in different network scenarios However one clone cannot be suitable for each case So this paper has investigated the characteristics of the mentioned clones and calculated throughputs of them in simulated environment varying various performances metrics such as delay buffer size error rate number of traffic and bandwidth for finding which one is the best for what scenario The performance of these clones for varying network conditions and settings can effectively be evaluated using NS-2 In this work by doing simulation in NS-2 environment the throughputs of some exiting TCP implementations are calculated considering various metrics and then the calculated throughputs are compared among one another These comparisons show that which one is suitable in which case