Text-Independent Speaker Verification Based on Information Theoretic Learning

In this paper VQ (Vector Quantization) based on information theoretic learning is investigated for the task of text-independent speaker verification. A novel VQ method based on the IT (Information Theoretic) principles is used for the task of speaker verification and compared with two classical VQ approaches: the K-means algorithm and the LBG (Linde Buzo Gray) algorithm. The paper provides a theoretical background of the vector quantization techniques, which is followed by experimental results illustrating their performance. The results demonstrated that the ITVQ (Information Theoretic Vector Quantization) provided the best performance in terms of classification rates, EER (Equal Error Rates) and the MSE (Mean Squared Error) compare to Kmeans and the LBG algorithms. The outstanding performance of the ITVQ algorithm can be attributed to the fact that the IT criteria used by this algorithm provide superior matching between distribution of the original data vectors and the codewords

Clustering and Fault Tolerance for Target Tracking using Wireless Sensor Networks

Over the last few years, the deployment of WSNs (Wireless Sensor Networks) has been fostered in diverse applications. WSN has great potential for a variety of domains ranging from scientific experiments to commercial applications. Due to the deployment of WSNs in dynamic and unpredictable environments. They have potential to cope with variety of faults. This paper proposes an energy-aware fault-tolerant clustering protocol for target tracking applications termed as the FTTT (Fault Tolerant Target Tracking) protocol. The identification of RNs (Redundant Nodes) makes SN (Sensor Node) fault tolerance plausible and the clustering endorsed recovery of sensors supervised by a faulty CH (Cluster Head). The FTTT protocol intends two steps of reducing energy consumption: first, by identifying RNs in the network; secondly, by restricting the numbers of SNs sending data to the CH. Simulations validate the scalability and low power consumption of the FTTT protocol in comparison with LEACH protocol

Decentralized Hierarchical Controller Design for Selective Damping of Inter Area Oscillations Using PMU Signals

This paper deals with the decentralized hierarchical PSS (Power System Stabilizer) controller design to achieve a better damping of specific inter-area oscillations. The two-level decentralized hierarchical structure consists of two PSS controllers. The first level controller is a local PSS controller for each generator to damp local mode in the area where controller is located. This controller uses only local signals as input signals. The local signal comes from the generator at which the controller is located. The secondary level controller is a multivariable decentralized global PSS controller to damp inter-area modes. This controller uses selected suitable wide area PMU (Phasor Measurement Units) signals as inputs. The PMU or global signals are taken from network locations where the oscillations are well observable. The global controller uses only those global input signals in which the assigned single inter-area mode is most observable and is located at a generator that is most effective in controlling the assigned mode. The global controller works mainly in a frequency band given by the natural frequency of the assigned mode. The effectiveness of the resulting hierarchical controller is demonstrated through simulation studies conducted on a test power system