Tianzan Li’s research while affiliated with Changsha University of Science and Technology and other places

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Publications (2)


Non-synchronous Signal Monitoring Based on Simulated Annealing Neural Network
  • Conference Paper

August 2009

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9 Reads

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3 Citations

Tianzan Li

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Xiaohua Wang

A neural network method combined with simulated annealing algorithm is proposed for power system harmonic analysis. This method is aimed at the system in which the sampling frequency cannot be locked on the actual fundamental frequency. By updating the relevant parameters including the learning rate of fundamental frequency, fundamental frequency, harmonic phases and amplitudes, the accurate harmonic estimating results can be obtained. The simulating results show that the harmonic estimation accuracy by the proposed approach is relatively better than that by the conventional harmonic analysis methods in the asynchronous case.


A new approach for designing 2-D quasi-equiripple zero-phase FIR digital filters

November 2008

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29 Reads

Proceedings of SPIE - The International Society for Optical Engineering

A batch back-propagation neural networks (BBPNN) approach was presented to design general two-dimensional (2-D) quasi-equripple zero-phase finite-impulse response (FIR) digital filters. By minimizing the frequency-domain weighted error function, the BBPNN design method was obtained. The solution was presented as a parallel algorithm to approximate the desired frequency response specification. Thus, the method makes a fast calculation of the filter's coefficients possible. It is shown that the method leads to an optimal solution for the filter coefficients. The implementation of the approach was described together with some design guidelines, and some optimal design examples were given to demonstrate the effectiveness of the proposed approach.

Citations (1)


... Further, four objective functions to measure the performance of the detection platform were set as follows: the magnetic flux density, the uniformity of the magnetic flux density, the Bx component of magnetic flux density, and the uniformity of the Bx component of magnetic flux density in the circular wafer area where the MNP device was located. The MNP detection platform applies a static uniform magnetic field (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) to the MNP device through the Helmholtz coil structure [27], and the magnetic field generated by a current-carrying conductor can be calculated through the Biot-Savart law, as shown in Equation (1). ...

Reference:

A Method and Device for Detecting the Number of Magnetic Nanoparticles Based on Weak Magnetic Signal
Non-synchronous Signal Monitoring Based on Simulated Annealing Neural Network
  • Citing Conference Paper
  • August 2009