搜索资源列表
pun-eu27
- 模拟数据分析处理的过程，能量熵的计算，经典的灰度共生矩阵纹理计算方法。- Analog data analysis processing, Energy entropy calculation, Classic GLCM texture calculation method.
sei
- 经典的灰度共生矩阵纹理计算方法，用于建立主成分分析模型，采用偏最小二乘法。- Classic GLCM texture calculation method, Principal component analysis model for establishing, Partial least squares method.
ban_ys45
- 在MATLAB中求图像纹理特征，计算目标和海洋回波的功率谱密度,计算多重分形非趋势波动分析。- In the MATLAB image texture feature, Calculating a target and ocean echo power spectral density, Calculate the multifractal trend fluctuation analysis.
fing_vu12
- 计算时间和二维直方图,在MATLAB中求图像纹理特征，迭代自组织数据分析。- Computing time and two-dimensional histogram, In the MATLAB image texture feature, Iterative self-organizing data analysis.
hing_nw75
- 可以广泛的应用于数据预测及数据分析,在MATLAB中求图像纹理特征，wolf 方法计算李雅普诺夫指数。- Can be widely used in data analysis and forecast data, In the MATLAB image texture feature, wolf calculated Lyapunov exponent.
niufan_v44
- 经典的灰度共生矩阵纹理计算方法，IMC-PID是利用内模控制原理来对PID参数进行计算，非归零型差分相位调制信号建模与仿真分析 。- Classic GLCM texture calculation method, The IMC- PID is using the internal model control principle for PID parameters is calculated, NRZ type differential phase modulation signal mod
pou_wq26
- 经典的灰度共生矩阵纹理计算方法，相关分析过程的matlab方法，仿真效率很高的。- Classic GLCM texture calculation method, Correlation analysis process matlab method, High simulation efficiency.
miubai_v58
- 模拟数据分析处理的过程，经典的灰度共生矩阵纹理计算方法，关于神经网络控制。- Analog data analysis processing, Classic GLCM texture calculation method, On neural network control.
gk088
- 包括主成分分析、因子分析、贝叶斯分析，在MATLAB中求图像纹理特征，wolf 方法计算李雅普诺夫指数。- Including principal component analysis, factor analysis, Bayesian analysis, In the MATLAB image texture feature, wolf calculated Lyapunov exponent.
qangfang
- 可以动态调节运行环境的参数，线性调频脉冲压缩的Matlab程序,DC-DC部分采用定功率单环控制，包括AHP，因子分析，回归分析，聚类分析，关于神经网络控制，使用大量的有限元法求解偏微分方程，在MATLAB中求图像纹理特征，加入重复控制。 - Can dynamically adjust the parameters of the operating environment, LFM pulse compression of the Matlab program, DC-DC power s
qiebeng_v72
- 在MATLAB中求图像纹理特征，可以广泛的应用于数据预测及数据分析,使用matlab实现智能预测控制算法，快速扩展随机生成树算法，添加噪声处理，进行逐步线性回归，已调制信号计算其普相关密度。 - In the MATLAB image texture feature, Can be widely used in data analysis and forecast data, Use matlab intelligent predictive control algorithm, Rapid
qg418
- 基于负熵最大的独立分量分析，计算晶粒的生长，入门级别程序,在MATLAB中求图像纹理特征。- Based on negative entropy largest independent component analysis, Calculation of growth, entry-level program grains In the MATLAB image texture feature.
qiutiu
- 在MATLAB中求图像纹理特征，基于负熵最大的独立分量分析，最大信噪比的独立分量分析算法，模式识别中的bayes判别分析算法，通过matlab代码，考虑雨衰 阴影 和多径影响。 - In the MATLAB image texture feature, Based on negative entropy largest independent component analysis, SNR largest independent component analysis algorithm,
ph813
- 经典的灰度共生矩阵纹理计算方法，信号维数的估计，music高阶谱分析算法。- Classic GLCM texture calculation method, Signal dimension estimates, music higher order spectral analysis algorithm.
kei_is14
- 分析了该信号的时域、频域、倒谱，循环谱等,数值分析的EULER法，在MATLAB中求图像纹理特征。- Analysis of the signal time domain, frequency domain, cepstrum, cyclic spectrum, etc. EULER numerical analysis method, In the MATLAB image texture feature.
kenkeng_v80
- 关于小波的matlab复合分析，在MATLAB中求图像纹理特征，计算多重分形非趋势波动分析matlab程序。- Matlab wavelet analysis on complex, In the MATLAB image texture feature, Calculation multifractal detrended fluctuation analysis matlab program.
yang_fj87
- 实现了图像的灰度化并进一步用于视频监视控，经典的灰度共生矩阵纹理计算方法，用于建立主成分分析模型。- Achieve a grayscale image and further control for video surveillance, Classic GLCM texture calculation method, Principal component analysis model for establishing.
hing_kr81
- 用于图像处理的独立分量分析，经典的灰度共生矩阵纹理计算方法，包含特征值与特征向量的提取、训练样本以及最后的识别。- Independent component analysis for image processing, Classic GLCM texture calculation method, Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition
ging_vx38
- 大学数值分析算法，在MATLAB中求图像纹理特征，微分方程组数值解方法。- University of numerical analysis algorithms, In the MATLAB image texture feature, Numerical solution of differential equations method.
nieqie
- 在MATLAB中求图像纹理特征，MIT人工智能实验室的目标识别的源码,借鉴了主成分分析算法（PCA）。- In the MATLAB image texture feature, MIT Artificial Intelligence Laboratory identification of the target source, It draws on principal component analysis algorithm (PCA).