Lushhttp://mloss.orgUpdates and additions to LushenMon, 12 Nov 2007 06:35:08 -0000Lush 1.2.1<html><p>Lush is an object-oriented Lisp dialect with a super-simple way of integrating C/C++ code and libraries. It includes extensive libraries for numerical computing, machine learning, and computer vision. </p> <p>If you do research and development in signal processing, image processing, machine learning, computer vision, bio-informatics, data mining, statistics, simulation, optimization, or artificial intelligence, and feel limited by Matlab and other existing tools, Lush is for you. If you want a simple environment to experiment with graphics, video, and sounds, Lush is for you. </p> <p>Lush is designed to be used in situations where one would want to combine the flexibility of a high-level, weakly-typed interpreted language (a dialect of Lisp), with the efficiency of a strongly-typed, natively-compiled language, and with the easy integration of code written in C, C++, or other languages. </p> <p>Lush's main features includes: </p> <ul> <li> A very clean, simple, and easy to learn Lisp-like syntax. </li> <li> A compiler that produces very efficient C code and relies on the C compiler to produce efficient native code (no inefficient bytecode or virtual machine). </li> <li> An easy way to interface C functions and libraries, and a powerful dynamic linker/loader for object files or libraries (.o, .a and .so files) written in other compiled languages. </li> <li> The ability to freely mix Lisp and C in a single function. </li> <li> A powerful set of vector/matrix/tensor operations. </li> <li> A huge library of over 10,000 numerical routines, including full interfaces to GSL, LAPACK, and BLAS. </li> <li> A library of image and signal processing routines. </li> <li> An extensive set of graphic routines, including an object-oriented GUI toolkit, an interface to OpenGL/GLU/GLUT, and the OpenInventor scene rendering engine. </li> <li> An interface to the Simple Directmedia Layer (SDL) multimedia library, including a sprite class with pixel-accurate collision detection (perfect for 2D games). </li> <li> Sound and video grabbing (using ALSA and Video4Linux). </li> <li> Several libraries for machine learning, neural net (including convolutional nets), statistical estimation, Hidden Markov Models, kernel methods (gblearn2, Torch, HTK, SVM). </li> <li> libraries for computer vision (OpenCV) </li> </ul></html>Leon Bottou, Yann LeCunMon, 12 Nov 2007 06:35:08 -0000 learninggraphsequence analysisstructured outputssvmclassificationpreprocessing