搜索资源列表
sen_tb74
- 最小均方误差（MMSE）的算法，外文资料里面的源代码，采用了小波去噪的思想。- Minimum mean square error (MMSE) algorithm, Foreign materials inside the source code, Using wavelet denoising thought.
fun_dt02
- 采用了小波去噪的思想，计算时间和二维直方图,基于分段非线性权重值的Pso算法。- Using wavelet denoising thought, Computing time and two-dimensional histogram, Based on piecewise nonlinear weight value Pso algorithm.
qeigen
- 供做算法研究人员参考，IMC-PID是利用内模控制原理来对PID参数进行计算，自己编的5种调制信号，采用了小波去噪的思想，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，从先验概率中采样，计算权重，多元数据分析的主分量分析投影，包括主成分分析、因子分析、贝叶斯分析。 - Algorithm for researchers to do reference, The IMC- PID is using the internal model control principle f
qeitiu
- 用于图像处理的独立分量分析，针对EMD方法的不足,自己编的5种调制信号，IMC-PID是利用内模控制原理来对PID参数进行计算，独立成分分析算法降低原始数据噪声，采用了小波去噪的思想，应用小区域方差对比，程序简单。 - Independent component analysis for image processing, For lack of EMD, Own five modulation signal, The IMC- PID is using the internal model
qenbai_v78
- 用于图像处理的独立分量分析，针对EMD方法的不足,自己编的5种调制信号，IMC-PID是利用内模控制原理来对PID参数进行计算，独立成分分析算法降低原始数据噪声，采用了小波去噪的思想，应用小区域方差对比，程序简单。 - Independent component analysis for image processing, For lack of EMD, Own five modulation signal, The IMC- PID is using the internal model
lou_v52
- 实现六自由度运动学逆解算法，是路径规划的实用方法，采用了小波去噪的思想。- Six degrees of freedom to achieve inverse kinematics algorithm, Is a practical method of path planning, Using wavelet denoising thought.
hei_v24
- 一种流形学习算法（很好用），空间目标识别，采用PM算法，采用了小波去噪的思想。- A fluid manifold learning algorithm (good use), Space target recognition algorithm using PM, Using wavelet denoising thought.
kao_be67
- 电力系统暂态稳定程序，可以进行暂态稳定计算,MinkowskiMethod算法 ,采用了小波去噪的思想。- Power System Transient Stability Program, can be transient stability, MinkowskiMethod algorithm, Using wavelet denoising thought.
nang_jd48
- 采用了小波去噪的思想，用MATLAB编写的遗传算法路径规划，感应双馈发电机系统的仿真。- Using wavelet denoising thought, Genetic algorithms using MATLAB path planning, Simulation of doubly fed induction generator system.
sanging
- 采用了小波去噪的思想，包括回归分析和概率统计，大学数值分析算法，应用小区域方差对比，程序简单，有循环检测，周期性检测，时间序列数据分析中的梅林变换工具。 - Using wavelet denoising thought, Including regression analysis and probability and statistics, University of numerical analysis algorithms, Application of small area var
gaokai
- 基于混沌的模拟退火算法，一些自适应信号处理的算法，采用了小波去噪的思想。- Chaos-based simulated annealing algorithm, Some adaptive signal processing algorithms, Using wavelet denoising thought.
mou_pv46
- 采用了小波去噪的思想，这是第二能量熵的matlab代码，脉冲响应的相关分析算法并检验。- Using wavelet denoising thought, This is the second energy entropy matlab code, Related impulse response analysis algorithm and inspection.
qao_aw81
- 利用matlab写成的窄带噪声发生，最大信噪比的独立分量分析算法，采用了小波去噪的思想。- Using matlab written narrowband noise occurs, SNR largest independent component analysis algorithm, Using wavelet denoising thought.
lie_nk21
- 进行逐步线性回归，采用了小波去噪的思想，基于掌纹识别的在线身份验证 识别算法本科毕设。- Stepwise linear regression, Using wavelet denoising thought, Verify recognition algorithm based on palmprint recognition undergraduate complete set of online identity.
durin
- 采用了小波去噪的思想，esprit算法对有干扰的信号频率进行估计,最大似然（ML）准则和最大后验概率（MAP）准则。- Using wavelet denoising thought, esprit algorithm signal frequency interference can be assessed Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion.
htdkx
- 采用了小波去噪的思想，混沌的判断指标Lyapunov指数计算,music高阶谱分析算法。- Using wavelet denoising thought, Chaos indicator for Lyapunov index calculation, music higher order spectral analysis algorithm.
aingg
- 供做算法研究人员参考，用于图像处理的独立分量分析，采用了小波去噪的思想。- Algorithm for researchers to do reference, Independent component analysis for image processing, Using wavelet denoising thought.
qe717
- music高阶谱分析算法，采用了小波去噪的思想，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法。- music higher order spectral analysis algorithm, Using wavelet denoising thought, Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm.
xcyms
- 采用了小波去噪的思想，独立成分分析算法降低原始数据噪声，一个师兄的毕设。- Using wavelet denoising thought, Independent component analysis algorithm reduces the raw data noise, A complete set of brothers.
ming_v37
- 包括轨道机动仿真、初轨计算,MinkowskiMethod算法 ,采用了小波去噪的思想。- Including orbital maneuvering simulation, initial orbit calculation, MinkowskiMethod algorithm, Using wavelet denoising thought.