Time-frequency atom decomposition (TFAD) provides a flexible representation for non-
stationary signals, but the extremely high computational effort greatly blocks its practical …

The main problem of time-frequency atom decomposition (TFAD) lies in an extremely high
computational load. This paper pres-ents a fast implementation method based on quantum …

This paper uses an improved quantum-inspired genetic algorithm (IQGA) based time-
frequency atom decomposition to analyze the construction of radar emitter signals. With time …

In this paper, a novel approach to extract the features of radar emitter signals in the high
density, complex and variable signal modulation environment is presented. Based on the …

A hybrid chaotic quantum evolutionary algorithm is proposed to reduce amount of
computation, speed up convergence and restrain premature phenomena of quantum …

Timetabling is a well-known combinatorial optimization problem which belongs to the class
of NP hard problems. Quantum Evolutionary Algorithms (QEA) are highly suitable for the …

Feature extraction is the crucial technology to deinterleave and recognize the new system
radar emitter signals. In this paper, a novel time-frequency atom feature extraction approach …

To decrease the computational complexity and improve the search capability of quantum-
inspired evolutionary algorithm based on P systems (QEPS), a real-observation QEPS …

An effective approach based on the feature of time-frequency atoms for classification of the
radar emitter signals is presented. Firstly, we introduce a fast matching pursuit (MP) …

The fitness landscape of the timetabling problems is analyzed in this paper to provide some
insight into the properties of the problem. The analyses suggest that the good solutions are …