FFTW, a collection of fast C routines to compute the Discrete Fourier Transform in one or more dimensions.The fftw/ directory contains the source code for the complex transforms, and the rfftw/ directory contains the source code for the real transforms.
标签： collection Transform Discrete routines
上传时间： 2016-08-17
上传用户：yoleeson
DESCRIPTION : BIN to seven segments converter -- segment encoding -- a -- +---+ -- f | | b -- +---+ <- g -- e | | c -- +---+ -- d -- Enable (EN) active : high -- Outputs (data_out) active : low
标签： DESCRIPTION converter segments encoding
上传时间： 2016-08-17
上传用户：ainimao
This book provides a complete intermediate-level discussion of microcontroller programming using the C programming language. It covers both the adaptations to C necessary for targeting an embedded environment, and the common components of a successful development project. C is the language of choice for programming larger microcontrollers (MCU), those based on 32-bit cores. These parts are often derived from their general-purpose counterparts, and are both as complex and feature-rich. As a result, C (and C++) compilers are necessary and readily available for these MCUs. 是初学入们，嵌入式的好教材！@简单易懂
标签： intermediate-level microcontroller programming discussion
上传时间： 2013-12-18
上传用户：lo25643
The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Belief Propagation, Mean-Field approximation, and 4 monte-carlo sampling methods (Metropolis, Gibbs, Wolff, Swendsen-Wang). Use "help inference" from Matlab to see all options for usage. 2. gbp_preprocess.m and gbp.m These 2 interfaces split Generalized Belief Propagation into the pre-process stage (gbp_preprocess.m) and the inference stage (gbp.m), so the user may use only one of them, or changing some parameters in between. Use "help gbp_preprocess" and "help gbp" from Matlab. 3. simulatedAnnealing.m An interface to the simulated-annealing c-code. This code uses Metropolis sampling method, the same one used for inference. Use "help simulatedAnnealing" from Matlab.
标签： Matlab-interfaces inference interface the
上传时间： 2016-08-27
上传用户：gxrui1991
he algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.
标签： equivalent likelihood algorithm Sejnowski
上传时间： 2016-09-17
上传用户：Altman
本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006.
标签： incremental 编写 神经元网络 算法
上传时间： 2016-09-18
上传用户：litianchu
A clock writing by Verilog which can count from 00:00 to 23:59. With a C file to see the simulation results. A co-design example of C and Verilog.
标签： simulation Verilog writing clock
上传时间： 2016-10-12
上传用户：王者A
A code writing by Verilog which can find medium value. With a C file to see the simulation results. A co-design example of C and Verilog.
标签： simulation Verilog writing results
上传时间： 2014-11-18
上传用户：ljt101007
im2dat.m is used to convert images to data which can be plotted using the standard MATLAB functions. This is very handy if you have plots on hardcopy and you want to convert them into data that MATLAB can use. The scanned image can be analysed by this function and the output will allow you to perform any calculation/manipulations that MATLAB can perform, e.g. curve fitting.
标签： functions standard convert plotted
上传时间： 2014-12-07
上传用户：gdgzhym
Inside the C++ Object Model Inside the C++ Object Model focuses on the underlying mechanisms that support object-oriented programming within C++: constructor semantics, temporary generation, support for encapsulation, inheritance, and "the virtuals"-virtual functions and virtual inheritance. This book shows how your understanding the underlying implementation models can help you code more efficiently and with greater confidence. Lippman dispells the misinformation and myths about the overhead and complexity associated with C++, while pointing out areas in which costs and trade offs, sometimes hidden, do exist. He then explains how the various implementation models arose, points out areas in which they are likely to evolve, and why they are what they are. He covers the semantic implications of the C++ object model and how that model affects your programs.
上传时间： 2013-12-24
上传用户：zhouli
