资源列表
Deep Learning
- 深度学习（deep learning）英文专著，适合深度学习的理论基础学习。(A monographs which suitable for the theoretical basis of deep learning.)
tvar1
- 非平稳信号分析与处理,可用于特征提取，将AR模型扩展应用于非平稳时间序列，得到具有时变系数的时变自回归(time-varying autoregressive, TVAR)模型。(nonstationary random signal analysis and processing)
CA_Tustin_301025_1962_24000_geo.tif
- levy flight在智能算法上的应用(levy flight Applications in intelligent algorithms.)
zip~
- 机器学习实战教程！！！,包含教程的讲义，还有代码等等，比较实用的，你值得拥有。。。。。。。(A practical course for machine learning)
AprioriAll-Algorithm-master
- To reduce the generation of candidate sequences and the scans to sequence database for AprioriAll algorithm, an efficient sequential pattern mining method based on improved AprioriAll algorithm is presented. Firstly, data are preprocessed. Then do
PQ load flow
- MATLAB的潮流计算程序，14节点和30节点(MATLAB's power flow program, 14 nodes and 30 nodes)
ajss-3-2-3
- Apriori[1] is an algorithm for frequent item set mining and association rule learning over transactional databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as
IRJET-V4I5669
- The Apriori algorithm was proposed by Agrawal and Srikant in 1994. Apriori is designed to operate on databases containing transactions (for example, collections of items bought by customers, or details of a website frequentation). Other algorithms ar
STFT
- 短时傅里叶变换实现线性调频信号的时频分析(Time-frequency analysis of LFM signal by short time Fourier transform)
e119ead869b2fb015502ba4defc5b2f4
- Machine learning is a field of computer science that gives computer systems the ability to "learn" (i.e. progressively improve performance on a specific task) with data, without being explicitly programmed.
lib.tar
- 将训练之后的caffe model生成.so库文件，方便在工程中直接调用，不需要写caffe test分代码(he Caffe model after the training is generated for the.so library file, which is convenient to call in the project and does not need to write Caffe test code)
nlinfit+regress_data fitting
- 对农作物六种经典水分生产函数模型的相关数据进行拟合求函数中参数(Fitting the parameters of the six classical crop water production function models by fitting the related data)