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The compressed sensing (CS) paradigm unifies sensing and compression of sparse signals in a simple linear measurement step. Reconstruction of the signal from the CS measurements relies on the knowledge of the measurement matrix used for sensing. Generation of the pseudo-random sensing matrix utilizing a cryptographic key, offers a natural method for(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t This paper deals with the strategies for feature selection and(More)
In literature improvements in neural learning iirc rcportcd on, which have been achieved through input diitii m;inipuliition, based on entirely experimental studies. Theorcticzil background is not supplied for these studies and neural networks are employed as a " black box " model. Within this work, this problem is highlighted and the impact of the modified(More)
This paper is mainly concerned with an investigation of the suitability of Hopfield neural network structures in solving the power economic dispatch problem. For Hopfield neural network applications to this problem three important questions have been answered: what the size of the power system is; how efficient the computational method; and how to handle(More)
Emotion detection has gained increasing attention and become an active research area. The problem is solved with improved feature set with different number of feature groups, by employing different classifiers in order to achieve satisfactory recognition rate. In this study, speech related features are employed to evaluate the performance of different(More)
In this study, the performance of two neural classifiers; namely Multi Layer Perceptron (MLP) and Radial Basis Fuction (RBF), are compared for a multivariate classification problem. MLP and RBF are two of the most widely neural network architecture in literature for classification and have successfully been employed for a variety of applications. A(More)
In this paper, we propose two new frameworks, so as to boost the feature selection algorithms in a way that the selected features will be more informative in terms of class-separability. In the first framework, features that are more informative in discriminating an emotional class from the rest of the classes are favoured for selection by the feature(More)
The work explores the use of Hopfield neural network for a constrained economic dispatch problem with prohibited operating zones. Yalcinoz and Short 11 I discussed a special methodology to improve the performance of Hopfield networks for solving the unconstrained economic dispatch problem. I n this paper the improved Hopfield network is applied to the(More)
Color detection is generally a primary stage in most of the image processing application, if the application is based on the color information, such as road sign detection, face detection, skin color detection, object detection and object tracking etc. As the performance of subsequent modules in an image processing application is adversely affected by the(More)