Classical Text Editor Intro - D Programming Language - Digital Mars “It seems to me that most of the ‘new’ programming languages fall into one of two categories: Those from academia with radical new paradigms and those from large corporations with a focus on RAD and the web. Maybe it’s time for a new language born out of practical experience implementing compilers.” -- Michael “Great, just what I need.. another D in programming.” -- Segfault D is a systems programming language. The D language is statically typed and compiles directly to machine code. It is not governed by a corporate agenda or any overarching theory of programming. There are two versions of the language: D version 2 which is recommended for new projects. D version 1 which is in maintenance mode. There are currently four implementations: Digital Mars dmd for Windows 1.0 2.0 , x86 Linux 1.0 2.0 , Mac OS X 1.0 2.0 , and x86 FreeBSD 1.0 , 2.0 . LLVM D Compiler ldc for D version 1. Gnu D compiler gdc . D.NET compiler alpha for .NET for D version 2.
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Stanford Encyclopedia of Philosophy Gaussian process Gaussian processes are important in statistical modelling because of properties inherited from the normal. For example, if a random process is modelled as a Gaussian process, the distributions of various derived quantities can be obtained explicitly. Such quantities include: the average value of the process over a range of times; the error in estimating the average using sample values at a small set of times. Definition Some authors assume the random variables Xt have mean zero; this greatly simplifies calculations without loss of generality and allows the mean square properties of the process to be entirely determined by the covariance function K. Alternative definitions Alternatively, a process is Gaussian if and only if for every finite set of indices in the index set is Gaussian if and only if, for every finite set of indices , there are real valued with such that The numbers and Covariance functions Usual covariance functions Here . have to be for . See also
Community of Data Warehousing and Business Intelligence Professionals Online Etymology Dictionary Perlin noise Perlin noise is a computer-generated visual effect developed by Ken Perlin, who won an Academy Award for Technical Achievement for inventing it. It can be used to simulate elements from nature, and is especially useful in circumstances where computer memory is limited. Uses Two-dimensional slice through 3D Perlin noise. Development Perlin noise resulted from the work of Ken Perlin, who developed it at Mathematical Applications Group, Inc. Algorithm Perlin noise rescaled and added into itself to create fractal noise. Define an n-dimensional grid. In 2001, Ken Perlin created simplex noise, which is similar but uses a simpler space-filling grid, alleviating some problems with Perlin "classic noise", among them, computational complexity. Complexity When is the number of dimensions, Perlin noise has complexity , while simplex noise has complexity See also References Jump up ^ Kerman, Phillip. External links
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