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Chapter_3
说明： 好东东，可以和MIMO OFDM 联合使用(good, and the joint use of MIMO OFDM)
- 2005-11-12 14:26:15下载
- 积分：1
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solution-of--SR-
随机共振的Runge-Kutta解法，能够给出任意随机共振系统的响应信号，进而对系统做出分析。(Stochastic resonance of Runge-Kutta solution, able to give any response signal stochastic resonance system, and thus an analysis of the system.)
- 2011-10-20 21:46:29下载
- 积分：1
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istft_cf
A matlab function that calculates the inverse short term Fourier transform with adjustable parameters.
- 2009-09-26 04:21:36下载
- 积分：1
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CharacterRecongnize
说明： 特征提取，人的手的动作等，对这些数据进行捕捉，提取(Feature extraction, human hand movements, etc., these data capture, extraction)
- 2010-04-09 20:31:30下载
- 积分：1
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genhurstxx
Generalized Hurst exponent of a stochastic variable
- 2013-01-05 04:08:26下载
- 积分：1
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histogram
histogram code in matlab
- 2011-07-29 13:08:24下载
- 积分：1
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allmargin
Control code for matlab versions prior
- 2013-10-24 21:21:31下载
- 积分：1
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dbt2.21
MATLAB阵列信号处理工具箱DBT2-21 (MATLAB array signal processing toolbox DBT2-21)
- 2008-06-12 16:07:08下载
- 积分：1
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impacting-filter
雷达通信一体化系统，针对非波动目标以及波动目标的雷达探测性能分析。(he dual-frequency MPPSK-MODEM platform is a flexible one. When ranging accuracy request is low or platform is particularly affected by power limitations, the platform would perform both data transmission and range measurement with single frequency modes. In this paper, the ranging resolution of MPPSK pulse waveforms with the match filter and impacting filter processing method are discussed, respectively. Also, the selection of MPPSK modulation parameters for ranging is considered. In particular, requirements that allow for employing such special parameter values for range measurements with high accuracy and high range are investigated. Moreover, high repetition frequency (HRF) bi-phase code MPPSK pulse train base on m sequence are presented, the ranging accuracy of the proposed signal with the match filter processing method is deduced. In addition to theoretical considerations, the paper presents system simulations and measurement results of single-frequency MPPSK intergated systems, d)
- 2020-09-22 09:57:52下载
- 积分：1
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laplacian_eigen
Laplacian Eigenmaps [10] uses spectral techniques to perform dimensionality reduction. This technique relies on the basic assumption that the data lies in a low dimensional manifold in a high dimensional space.[11] This algorithm cannot embed out of sample points, but techniques based on Reproducing kernel Hilbert space regularization exist for adding this capability.[12] Such techniques can be applied to other nonlinear dimensionality reduction algorithms as well.
- 2011-01-23 02:17:08下载
- 积分：1
