Design of Low-Noise and High-Density Signal Intelligent Detection System

Abstract:

Using motion state of the equipment transducer to determine the presence of a weak signal is a common method of signal detection, whose core is to determine the system's phase change. There a many traditional ways to judge phase transition, but most of which have computational complexity and need a large amount of data which make them difficult to apply engineering practices. In order to solve these problems, this paper presents a detection method based on Lyapunov exponent classification with a small amount of data. This approach has some advantages such as requiring fewer observed values, small calculation amount, and able to automatically determine the phase transition without subjective factors involved etc. Experiments show that this method has stable performance, high effectiveness, strong practicality and promotion.

• Periodical: Advanced Materials Research (Volumes 760-762)
• Pages: 2229-2233
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.760-762.2229
• Online since: September 2013
• Authors: Xiaoan Yang
• Keywords: Classification, Small Amount of Data, Weak Signal

References

[1] Ventura D, Martinez T R. Quantum Associative Memory[J]. Information Sciences, 2000, 12(4): 273-296.

[2] DiVincenzo D. Two-Bit Gatesare Universal for Quantum Computation, Phys Rev, 1995, 5(1): 1015-1022.

[3] Narayanan A, Menner T. Quantum Artificial Neral Network Architectures and Components. Information Sciences, 2000, 128(3-4): 231-255.

DOI: 10.1016/s0020-0255(00)00055-4

[4] Behrman E C, Niemel J, Skinner S R A. Quantum Dot Neural Network. Proceeding Of the 4th Workshop on Physicsof Computation, 22-24, (1996).

[5] Kouda, N, Matsui, N, Nishimura H. Learning performance of neuron model based on quantum superposition. Proceedings of the 2000 IEEE International Workshop on Robot and Human Interactive Communication, 2000, 112–117.

DOI: 10.1109/roman.2000.892480