搜索结果

用Java实现的一个简单的寄存器分配器，用的算法是线性扫描(Linear Scan)

外国人开发的电磁时域有限差分方法工具包 Electromagnetic Finite-Difference Time-Domain (EmFDTD) is a basic two-dimensional FDTD code developed at the School of Electrical Engineering, Sharif University of Technology. This code has been written based on the standard Yee s FDTD algorithm. Applicati ...

The inverse of the gradient function. I ve provided versions that work on 1-d vectors, or 2-d or 3-d arrays. In the 1-d case I offer 5 different methods, from cumtrapz, and an integrated cubic spline, plus several finite difference methods. In higher dimensions, only a finite difference/linear alge ...

Boost provides free peer-reviewed portable C++ source libraries. We emphasize libraries that work well with the C++ Standard Library. Boost libraries are intended to be widely useful, and usable across a broad spectrum of applications. The Boost license encourages both commercial and non-commercial ...

MATLAB Code for Optimal Quincunx Filter Bank Design Yi Chen July 17, 2006 This file introduces the MATLAB code that implements the two algorithms (i.e., Algorithms 1 and 2 in [1], or Algorithms 4.1 and 4.2 in [2]) used for the construction of quincunx filter banks with perfect reconstruction, linear ...

H.264/AVC, the result of the collaboration between the ISO/IEC Moving Picture Experts Group and the ITU-T Video Coding Experts Group, is the latest standard for video coding. The goals of this standardization effort were enhanced compression efficiency, network friendly video representation for inte ...

measure through the cross-entropy of test data. In addition, we introduce two novel smoothing techniques, one a variation of Jelinek-Mercer smoothing and one a very simple linear interpolation technique, both of which outperform existing methods.

Batch version of the back-propagation algorithm. ％ Given a set of corresponding input-output pairs and an initial network ％ [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the ％ network with backpropagation. ％ ％ The activation functions must be either linear or tanh. The network ...

％ Train a two layer neural network with the Levenberg-Marquardt ％ method. ％ ％ If desired, it is possible to use regularization by ％ weight decay. Also pruned (ie. not fully connected) networks can ％ be trained. ％ ％ Given a set of corresponding input-output pairs and an initial ％ network, ％ ...

Train a two layer neural network with a recursive prediction error ％ algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully ％ connected) networks can be trained. ％ ％ The activation functions can either be linear or tanh. The network ％ architecture is defined by the matrix NetDef , w ...