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Hilbert Transformation Impulse Response

Sulima M.

Image Processing & Communications

2014

Vol. 19, no. 4

27--35

This work presents a new DHT impulse response function based on the proposed nonlinear equation system obtained as a result of combining the DHT and IDHT equation systems. In the case of input time series with selected characteristics, the DHT results obtained using this impulse response function are characterised by a higher accuracy compared to the DHT results obtained based on the convolution using other known DHT impulse response functions. The results are also characterised by a higher accuracy than the DHT results obtained using the popular indirect DHT method based on discrete Fourier transform (DFT). Analysis of these example time series with selected characteristics was performed based on the signal-to-noise ratio.

Leader Glowworm Swarm Optimization Algorithm for Solving Nonlinear Equations Systems

Zhou Y., Liu J., Zhao G.

Przegląd Elektrotechniczny

2012

R. 88, nr 1b

101-106

This paper presents a leader glowworm swarm optimization algorithm (LGSO) for solving nonlinear equations systems. Since glowworm swarm optimization algorithm has bad optimized ability at high dimension, proposing glowworm swarm optimization algorithm with leader mechanism to strengthen the global optimization ability. Through various types nonlinear equations testing, experiment results show that the proposed algorithm has strong global searching capability and quickly finding the solutions of the equations, thus obviously improving the optimization global ability.

Zaprezentowano optymalizacyjny algorytm mrówkowy “świetlikowy” do rozwiązywania system równań nieliniowych. Ponieważ algorytm ten ma słabe możliwości optymalizacyjne przy dużych rozmiarach wprowadzono wspomagający mechanizm prowadzący „leader”.

Validating UPML Concepts in a Multi-agent Architecture

Sandru C., Negru V.

Schedae Informaticae

2006

Vol. 15

109-125

The task oriented reasoning represents a powerful design paradigm. This research starts from a representative research in the area, the Unified Problem-Solving Method Development Language (UPML), and proposes a multi-agent architecture to support this ap- proach. The paper first models an applicative program, solving non- linear equation systems, using UPML concepts and then instantiates the proposed generic multi-agent architecture in order to generate a multi-agent system to solve the proposed problem.