We present analytical and experimental results for the scalability of 2-D discrete wavelet transform algorithms on coarse-grained parallel architectures. The principal operation in the 2-D DWT is the filtering operation used to implement the filter banks of the 2-D subband decomposition. We derive analytical results comparing time domain and frequency domain parallel algorithms for realizing th...

A general use of the adaptive optics requires an artificial guide star created by focusing a laser beam tuned to the sodium D2 line. We propose here a system to monitor the column density of the mesospheric sodium layer which is based on the sodium magneto-optical filter already widely used in solar observations. The principal characteristics of this system are high transmission and high spectr...

Myocardial Infarction is a vital disease that needs to be intervened in very short time. The analysis of the patient's electrocardiography (ECG) data has an important place diagnosis. For this reason, computer aided decision support systems have been used recent years order determine more quickly and accurately. In study, classification was made using convolutional neural network algorithms on ...

A new approach to adaptive control is proposed. The principal distinguishing feature is the direct estimation and updating of the criterion function by means of a filtering operation on a vector of transitional pseudo-return functions. The data storage and computational problems often associated with explicit probability distrib ution updating via Bayes’ rule are thus avoided. Convergence prope...

The selection of appropriate wavelets is an important target for any application. In this paper Face recognition has been performed using Principal component analysis (PCA), Gaussian based PCA and Gabor based PCA. PCA extracts the relevant information from complex data sets and provides a solution to reduce dimensionality. PCA is based on Euclidean distance calculation which is minimized by app...

A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximat...

Oriented PCA (OPCA) extends standard Principal Component Analysis by maximizing the power ratio of a pair of signals rather than the power of a single signal. We show that OPCA in combination with almost arbitrary temporal filtering can be used for the blind separation of linear instantaneous mixtures. Although the method works for almost any filter, the design of the optimal temporal filter is...

Vx = {yeP:xSy} is the principal filter generated by x. The filters on P are easily seen to be the open sets for a topology on P, and the increasing maps from P to another locally finite partially ordered set Q are precisely the continuous functions from P to Q [5]. For each filter V on P, let M(P9 V\ or simply M(V) when reference to P is understood, denote the free abelian group on V. For filte...

The selection of appropriate wavelets is an important target for any application. In this paper Face recognition has been performed using Principal component analysis (PCA), Gaussian based PCA and Gabor based PCA. PCA extracts the relevant information from complex data sets and provides a solution to reduce dimensionality. PCA is based on Euclidean distance calculation which is minimized by app...

A dynamic fundamental model was developed linking processes from the microscopic scale to the equipment scale for batch froth flotation. State estimation, fault detection, and disturbance identification were implemented using the extended Kalman filter (EKF), which reconciles real-time measurements with dynamic models. The online measurements for the EKF were obtained through image analysis of ...