electromagnetic_field_numerical

The book is divided into three parts: theory, method and implementation. Starting with a summary of the state-of-the-art in mobile technologies, the first part analyses their impacts on cartography and pinpoints the missing theories concerned with the development of map-based mobile services. A conceptual framework of mobile cartography is then introduced with the emphasis on mobile usage context. The second part is devoted to the design methodology under the constraints defined in the theoretical framework. A core issue deals with personalised mobile map services. The final part demonstrates the feasibility of the methods by using application scenarios.

股指期货套利系统开发程序,用matlab开发完成(index arbitrage system programme with matlab langauge )

蚁群算法, 求解旅行商问题matlab源程序， 31个城市，直接运行(Source of ant colony algorithm for TSP, Can be run directly,matlab,Traveling Salesman Problem,Ant Colony Algorithm,matlab program,31 city)

GIVENS ALGORITHM MATLAB

matlab直接打靶法，适用于最优控制。解决小车定点停车问题。(Matlab direct shooting method, applied to the optimal control.Solve the problem of car parking)

some soucre code for clustering

Gerald Teschl s matlab files for german book: "Mathematik für Informatiker 1: Diskrete Mathematik und lineare Algebra" ISBN "9783540774310"

In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. (In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. )

Fast Sparse LU substitution

This model simulate voltage sag when starting motor.