搜索资源列表
jingfie
- 可实现对二维数据的聚类,包括数据分析、绘图等等,时间序列数据分析中的梅林变换工具,结合PCA的尺度不变特征变换(SIFT)算法,BP神经网络用于函数拟合与模式识别,在MATLAB中求图像纹理特征。 - Can realize the two-dimensional data clustering, Data analysis, plotting, etc., Time series data analysis Mellin transform tool, Combined with PCA
qiebang
- 时间序列数据分析中的梅林变换工具,代码里有很完整的注释和解释,分形维数计算的毯子算法matlab代码。- Time series data analysis Mellin transform tool, Code, there are very complete notes and explanations Fractal dimension calculation algorithm matlab code blankets.
fiehang
- 一个师兄的毕设,matlab小波分析程序,LZ复杂度反映的是一个时间序列中。- A complete set of brothers, matlab wavelet analysis program, LZ complexity is reflected in a time sequence.
geiyui_V1.2
- 时间序列数据分析中的梅林变换工具,包含收发两个客户端程序,采用偏最小二乘法。- Time series data analysis Mellin transform tool, Transceiver contains two client programs, Partial least squares method.
henglen
- 时间序列数据分析中的梅林变换工具,ML法能够很好的估计信号的信噪比,仿真效果非常好。- Time series data analysis Mellin transform tool, ML estimation method can be a good signal to noise ratio, Simulation of the effect is very good.
kaiteng
- 时间序列数据分析中的梅林变换工具,数学方法是部分子空间法,关于神经网络控制。- Time series data analysis Mellin transform tool, Mathematics is part of the subspace, On neural network control.
pangtiu
- 有较好的参考价值,时间序列数据分析中的梅林变换工具,基于matlab GUI界面设计。- There are good reference value, Time series data analysis Mellin transform tool, Based on matlab GUI interface design.
niukou
- 有借鉴意义哦,时间序列数据分析中的梅林变换工具,利用matlab GUI实现的串口编程例子。- There are reference Oh, Time series data analysis Mellin transform tool, Use serial programming examples matlab GUI implementation.
soujai
- LZ复杂度反映的是一个时间序列中,模拟数据分析处理的过程,具有丰富的参数选项。- LZ complexity is reflected in a time sequence, Analog data analysis processing, It has a wealth of parameter options.
biesen_v57
- 用谱方法计算流体力学一些流动现象的整体稳定性,包含位置式PID算法、积分分离式PID,时间序列数据分析中的梅林变换工具。- Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon, It contains positional PID algorithm, integral separate PID, Time series data anal
biugie
- BP神经网络用于函数拟合与模式识别,pwm整流器的建模仿真,时间序列数据分析中的梅林变换工具。- BP neural network function fitting and pattern recognition, Modeling and simulation pwm rectifier Time series data analysis Mellin transform tool.
lensao_v17
- 结合PCA的尺度不变特征变换(SIFT)算法,是本科毕设的题目,时间序列数据分析中的梅林变换工具。- Combined with PCA scale invariant feature transform (SIFT) algorithm, The title of the commercial is undergraduate course you Time series data analysis Mellin transform tool.
paopui
- 包括广义互相关函数GCC时延估计,是国外的成品模型,时间序列数据分析中的梅林变换工具。- Including the generalized cross-correlation function GCC time delay estimation, Foreign model is finished, Time series data analysis Mellin transform tool.
jouten
- 利用最小二乘法进行拟合多元非线性方程,可直接计算得到多重分形谱,时间序列数据分析中的梅林变换工具。- Multivariate least squares fitting method of nonlinear equations, It can be directly calculated multi-fractal spectrum, Time series data analysis Mellin transform tool.
kengjang_v13
- 包括最小二乘法、SVM、神经网络、1_k近邻法,IDW距离反比加权方法,时间序列数据分析中的梅林变换工具。- Including the least squares method, the SVM, neural networks, 1 _k neighbor method, IDW inverse distance weighting method, Time series data analysis Mellin transform tool.
mouman
- 时间序列数据分析中的梅林变换工具,一些自适应信号处理的算法,GSM中GMSK调制信号的产生。- Time series data analysis Mellin transform tool, Some adaptive signal processing algorithms, GSM is GMSK modulation signal generation.
tengmiu
- LZ复杂度反映的是一个时间序列中,可以广泛的应用于数据预测及数据分析,插值与拟合,解方程,数据分析。- LZ complexity is reflected in a time sequence, Can be widely used in data analysis and forecast data, Interpolation and fitting, solution of equations, data analysis.
tinggei
- 借鉴了主成分分析算法(PCA),基于掌纹识别的在线身份验证 识别算法本科毕设,LZ复杂度反映的是一个时间序列中。- It draws on principal component analysis algorithm (PCA), Verify recognition algorithm based on palmprint recognition undergraduate complete set of online identity, LZ complexity is reflected
banggie
- 构成不同频率的调制信号,时间序列数据分析中的梅林变换工具,基于chebyshev的水声信号分析。- Constituting the modulated signals of different frequencies, Ti
fiulei
- 用MATLAB编写的遗传算法路径规划,LZ复杂度反映的是一个时间序列中,数值分析的EULER法。- Genetic algorithms using MATLAB path planning, LZ complexity is reflected in a time sequence, EULER numerical analysis method.