Current Issue : April - June Volume : 2013 Issue Number : 2 Articles : 7 Articles
The detection and tracking of moving objects (DATMO) in an outdoor environment from a mobile robot are\r\ndifficult tasks because of the wide variety of dynamic objects. A reliable discrimination of mobile and static\r\ndetections without any prior knowledge is often conditioned by a good position estimation obtained using Global\r\nPositionning System/Differential Global Positioning System (GPS/DGPS), proprioceptive sensors, inertial sensors or\r\neven the use of Simultaneous Localization and Mapping (SLAM) algorithms. In this article a solution of the DATMO\r\nproblem is presented to perform this task using only a microwave radar sensor. Indeed, this sensor provides\r\nimages of the environment from which Doppler information can be extracted and interpreted in order to obtain\r\nnot only velocities of detected objects but also the robot�s own velocity....
We present a method for coding speech signals for the simulation of a cochlear implant. The method is based on a wavelet packet\r\ndecomposition strategy. We used wavelet packet db4 for 7 levels, generated a series of channels with bandwidths exactly the same\r\nas nucleus device, and applied an input stimulus to each channel. The processed signal was then reconstructed and compared to\r\nthe original signal, which preserved the contents to a high percentage. Finally, performance of the wavelet packet decomposition\r\nin terms of computational complexity was compared to other commonly used strategies in cochlear implants. The results showed\r\nthe power of this method in processing of the input signal for implant users with less complexity than other methods, while\r\nmaintaining the contents of the input signal to a very good extent....
One of the most popular areas of study in pattern recognition which has now become the centre of many\r\nresearchers� attention is Writer Identification. A more recent development in the area is Twins Handwriting\r\nIdentification which has now become not only an important, but also widely popular area of study especially in\r\nthe fields of forensic research and biometrical identification. In terms of biometrical identification, it is known that a\r\npair of twins may share various similar traits genetically. Forensic evidence can be easily obtained from handwriting\r\nsamples. Therefore, in order to achieve reliable and accurate identification based on handwriting, it is important for\r\nthe similarities in the writing traits of a pair of twins to be differentiated. In identifying an individual, handwriting\r\nstyle can be analyzed to allow the implicit representation of the unique hidden features of the individual�s\r\nhandwriting. Said unique features can help in identifying the writer of the text which can be essential when\r\nidentifying the writer between a pair of twins. Previous studies in authorship identification were highly\r\nconcentrated in the study of the classification task as well as features extraction. However, the issue of the\r\nsimilarities in the traits of a pair of twins� handwriting were not taken into account thus, leaving a high possibility\r\nof degrading the performance of the classification process. Therefore, in order to achieve better input for the\r\nclassification task, this article will discuss an additional process which can better represent an individual�s personal\r\nfeatures through the transformation of the similarities via discretization protocol. The additional process can help\r\nimprove the level of identification for Individuality of Handwriting of a pair of twins....
In this article, we propose a new feature which could be used for the framework of SVM-based language\r\nrecognition, by introducing the idea of total variability used in speaker recognition to language recognition. We\r\nconsider the new feature as low-dimensional representation of Gaussian mixture model supervector. Thus we\r\npropose multiple total variability (MTV) language recognition system based on total variability (TV) language\r\nrecognition system. Our experiments show that the total factor vector includes the language dependent\r\ninformation; what�s more, multiple total factor vector contains more language dependent information.\r\nExperimental results on 2007 National Institute of Standards and Technology (NIST) Language Recognition\r\nEvaluation (LRE) databases show that MTV outperforms TV in 30 s tasks, and both TV and MTV systems can achieve\r\nperformance similar to that obtained by state-of-the-art approaches. Best performance of our acoustic language\r\nrecognition systems can be further improved by combining these two new systems....
The modified Riccati equation arises in the implementation of Kalman filter in target tracking under measurement uncertainty\r\nand it cannot be transformed into an equation of the form of the Riccati equation. An iterative solution algorithm of the modified\r\nRiccati equation is proposed. A method is established to decide when the proposed algorithm is faster than the classical one. Both\r\nalgorithms have the same behavior: if the system is stable, then there exists a steady-state solution, while if the system is unstable,\r\nthen there exists a critical value of the measurement detection probability, below which both iterative algorithms diverge. It is\r\nestablished that this critical value increases in a logarithmic way as the system becomes more unstable....
This paper investigates the characteristics of the Kalman filter for a broad class of complex Fibonacci systems and represents an\r\nextension to the complex domain of the state estimation problem for the real-valued Fibonacci system. Complex Fibonacci systems\r\nare obtained by modifying the real-valued Fibonacci recurrence relation to include complex coefficients, control and noise inputs,\r\nand a noisy output-measurement equation. Analytic expressions for the Kalman filter�s steady-state gain and error covariance\r\nmatrices are obtained, and it is found that for a broad subclass of these complex systems the elements of the matrices are functions\r\nof the golden ratio....
This article proposes a new modified anisotropic diffusion scheme for automatic defect detection in radiographic\r\nfilms. The new diffusion method allows to enhance, to sharpen anomalies, and to smooth the background of the\r\nimage. This new technique is based on the modification of the classical diffusion rule by using a nonlinear\r\nsigmoidal function. Experimental results are carried out on multiple real radiographic recorded films of Gaz\r\npipelines of the ââ?¬Å?Tunisian Society of Electricity and Gas distribution: STEGââ?¬Å? and the society ââ?¬Å?Control officesââ?¬â??chemical\r\nand industrial analysis laboratories: Saybolt-Tunisiaââ?¬Å?. The new automatic defect detection method shows good\r\nperformance in comparison with other existing algorithms....
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