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Implementation of adaptive generalized sidelobe cancellers using efficient complex valued arithmetic

George-Othon Glentis (2003)

International Journal of Applied Mathematics and Computer Science

Low complexity realizations of Least Mean Squared (LMS) error, Generalized Sidelobe Cancellers (GSCs) applied to adaptive beamforming are considered. The GSC method provides a simple way for implementing adaptive Linear Constraint Minimum Variance (LCMV) beamformers. Low complexity realizations of adaptive GSCs are of great importance for the design of high sampling rate, and/or small size and low power adaptive beamforming systems. The LMS algorithm and its Transform Domain (TD-LMS) counterpart...

Improving the stability of discretization zeros with the Taylor method using a generalization of the fractional-order hold

Cheng Zeng, Shan Liang, Yuzhe Zhang, Jiaqi Zhong, Yingying Su (2014)

International Journal of Applied Mathematics and Computer Science

Remarkable improvements in the stability properties of discrete system zeros may be achieved by using a new design of the fractional-order hold (FROH) circuit. This paper first analyzes asymptotic behaviors of the limiting zeros, as the sampling period T tends to zero, of the sampled-data models on the basis of the normal form representation for continuous-time systems with a new hold proposed. Further, we also give the approximate expression of limiting zeros of the resulting sampled-data system...

MRA super-wavelets.

Bildea, Stefan, Dutkay, Dorin Ervin, Picioroaga, Gabriel (2005)

The New York Journal of Mathematics [electronic only]

Multiple neural network integration using a binary decision tree to improve the ECG signal recognition accuracy

Hoai Linh Tran, Van Nam Pham, Hoang Nam Vuong (2014)

International Journal of Applied Mathematics and Computer Science

The paper presents a new system for ECG (ElectroCardioGraphy) signal recognition using different neural classifiers and a binary decision tree to provide one more processing stage to give the final recognition result. As the base classifiers, the three classical neural models, i.e., the MLP (Multi Layer Perceptron), modified TSK (Takagi-Sugeno-Kang) and the SVM (Support Vector Machine), will be applied. The coefficients in ECG signal decomposition using Hermite basis functions and the peak-to-peak...

Non-Lebesgue multiresolution analyses

Lawrence Baggett (2010)

Colloquium Mathematicae

Classical notions of wavelets and multiresolution analyses deal with the Hilbert space L²(ℝ) and the standard translation and dilation operators. Key in the study of these subjects is the low-pass filter, which is a periodic function h ∈ L²([0,1)) that satisfies the classical quadrature mirror filter equation |h(x)|²+|h(x+1/2)|² = 2. This equation is satisfied almost everywhere with respect to Lebesgue measure on the torus. Generalized multiresolution analyses and wavelets exist in abstract Hilbert...

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