资源列表
smartcar
- 基于飞思卡尔DG128单片机的智能寻线小车的完整版程序 供大家参考！-DG128 based on Freescale MCU Intelligent line trolley full version program for your reference!
wavelet_detect
- 极其经典的小波包分解程序，奇异点检测，附图说明-Most classical wavelet packet decomposition process, singular point detection, photo descr iption
InputOutput
- 实现对8为输入数据流，神经网络训练后，达到期望的目标值的过程。-Implementation of the 8 input data stream, neural network training, to achieve the desired target value of the process.
neural
- 類神經參考原始碼~沒有寫得很好,小點小問題,可自行修改-Neural reference source ~ not very well written, dot a small problem, can modify
wenxian
- 这些文献包括，分类，聚类，以及多目标优化，可以帮助大家进一步学习和接触此方面的知识，进而进一步发展-These documents include classification, clustering, and multi-objective optimization, which can help us to further study and access to the further development of this knowledge.
UncorrelatedDiscriminantNearestFeatureLineAnalysis
- 人脸识别文章 Uncorrelated Discriminant Nearest Feature Line Analysis for Face Recognition-Face article Uncorrelated Discriminant Nearest Feature Line Analysis for Face Recognition
OFNDA
- IEEE2010 人脸识别文章 OFNDA-IEEE2010 article OFNDA Face Recognition
L1normbased2dpCA
- IEEE2010 人脸识别文章 L1_norm based 2dpCA-IEEE2010 Face article L1_norm based 2dpCA
featurefusionuseingLLEforclassifaction
- 人脸识别文章 feature fusion useing LLE for classifaction-Face article feature fusion useing LLE for classifaction
FeatureExtractionUsingConstrained
- 人脸识别IEEE 2010论文，feature extraction use constraint approximation and supression-Face Recognition IEEE 2010 paper, feature extraction use constraint approximation and supression
chengxu
- 数字信号变换处理技术实现 研究数字信号离散傅里叶变换数字信号离散余弦变换数字信号离散希尔伯特变换数字信号Chirp Z变换。 -Digital signal processing technology transform Discrete Fourier transform of digital signal digital signal discrete cosine transform discrete Hilbert transform digital signal digital s
shijianxulie
- 时间序列的时频特性分析研究时间序列的傅里叶变换及逆变换，快速梅林变换及逆变换，短时离散傅里叶变换，得到瞬时频率。 研究时间序列的Born–Jondan时频分布图，Butterworth时频分布图，Choi–Williams时频分布图，得到瞬时频率。 -Time series analysis of time-frequency characteristics of time series of Fourier transform and inverse transform, the fa