The paper presents an improved variant of bacterial foraging optimization (BFO) named as Synchronous Bacterial Foraging Optimization (SBFO). The proposed SBFO is used to optimize multimodal and high dimensional functions. As all the bacteria update their information simultaneously, it has been named synchronous. A mutation operator proposed in this paper performs the global search. In SBFO, all bacteria process information independently in the same generation; hence parallel computers can be used to evaluate fitness values. The performance of SBFO is validated on a set of seven benchmark functions i.e. Sphere, Rosenbrock, Rastrigin, Griewank, Ackley, Schaffer's, Shekel's Foxholes. The results are compared with other published methods such as classical BFO, hybrid BFO (BSO), swarm-based algorithms, differential evaluation and Ashaker. The simulation results on benchmark functions show that the proposed optimization is capable of producing good quality global optima as compared to the above mentioned optimization techniques. The proposed method is a new variant of BFO and suitable for optimization of multimodal and high dimensional functions.

This paper presents the investigations of various broad banding and minimization techniques for square patch antenna. For bandwidth enhancement, square patch antenna with U shaped slot and L probe feed have been considered. Using these techniques, bandwidth in the range of 30 - 40% has been achieved. In addition to this, techniques to minimize patch antenna's surface area have also been analyzed. The shorting pin and shorting wall methods have been used for minimization. Simulation has been carried out using IE3D software.

Conventional Rake receiver is a popular and effective method of utilizing the diversity offered by a DS-CDMA and multipath communication channel. The proposed Rake receiver is useful for suppression of multiple access interference in a multipath channel. The receiver works on chip level equalization on each Rake finger to cancel multi-access interference. Simulation results show that the convergence, diversity gain and bit error probability performance of the proposed receiver is much better than conventional adaptive Rake receiver in multipath channels.

The periodic nonlinearity in nano-metrology systems based on heterodyne interferometers is the most important limitation to the accuracy of displacement measurement. It is mainly produced due to the polarization-mixing and frequency-mixing. In this paper, a new approach based on an ensemble of neural networks for modeling and compensation of nonlinearity in a high-resolution laser heterodyne interferometer is presented. We model the periodic nonlinearity arising from elliptical polarization and non-orthogonality of the laser polarized light based on the neural network approaches, including the multi-layer perceptrons and radial basis function as single neural networks and stacked generalization method as ensemble of neural networks. It is also shown that by using the stacked generalization method, the primary periodic nonlinearity of 1.3 nm is significantly compensated by a factor of 168.

This paper proposes a novel two-scale auditory feature based algorithm for non-intrusive evaluation of speech quality. The neuron firing probabilities along the length of the basilar membrane, from an explicit auditory model, are used to extract features from the distorted speech signal. This is in contrast to previous methods, which either use standard vocal tract based features, or incorporate only some aspects of the human auditory perception mechanism. The features are extracted at two scales, namely a global scale spanning all voiced frames in an utterance, and a local scale spanning voiced frames from contiguous voiced segments in the utterance. This is followed by a simple information fusion at the score level using Gaussian Mixture Models (GMMs). The use of an explicit auditory model to extract features is based on the premise that similar processing (in a qualitative sense) happens in human speech perception. In addition, auditory feature extraction at two scales incorporates the effects of both long term and short term distortions on speech quality. The proposed algorithm is shown to perform at least as good as the ITU-T Recommendation P.563.

This paper deals with the real time implementation of 11-level cascade multilevel inverter-based STATCOM using personal computer (PC) and ADD-ON cards for power system voltage control at the point of common coupling. Complete hardware and software development procedures have been explained in depth for direct as well as indirect control schemes. Experimental results are presented and it is shown that voltage control is achieved using cascade multilevel inverter based STATCOM, thus verifying the very basic purpose of STATCOM. Real time implementation using PC-based control technique has certain merits over digital signal processor based implementation, and some of these merits are high processing speed and low cost of implementation; therefore, PC-based implementation can be used in industry as well as for utility applications.