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They found that a C implementation of RDRAND ran about 2× slower than the default random number generator in C, and about 20× slower than the Mersenne Twister. Although a Python module of RDRAND has been constructed, it was found to be 20× slower than the default random number generator in Python, [ 20 ] although a performance comparison ...
A convolutional code that is terminated is also a 'block code' in that it encodes a block of input data, but the block size of a convolutional code is generally arbitrary, while block codes have a fixed size dictated by their algebraic characteristics. Types of termination for convolutional codes include "tail-biting" and "bit-flushing".
Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols is generated that cannot be reasonably predicted better than by random chance.
C, Java, C#, Fortran, Python 1970 many components Not free Proprietary: General purpose numerical analysis library. Math.NET Numerics: C. Rüegg, M. Cuda, et al. C#, F#, C, PowerShell 2009 4.7.0, November 2018 Free MIT/X11: General purpose numerical analysis and statistics library for the .NET framework and Mono, with optional support for ...
The Caltech 101 data set was used to train and test several computer vision recognition and classification algorithms. The first paper to use Caltech 101 was an incremental Bayesian approach to one-shot learning, [4] an attempt to classify an object using only a few examples, by building on prior knowledge of other classes.
It corrects the effect of agreement solely due to chance between clusterings, similar to the way the adjusted rand index corrects the Rand index. It is closely related to variation of information: [2] when a similar adjustment is made to the VI index, it becomes equivalent to the AMI. [1] The adjusted measure however is no longer metrical. [3]
The first class of turbo code was the parallel concatenated convolutional code (PCCC). Since the introduction of the original parallel turbo codes in 1993, many other classes of turbo code have been discovered, including serial concatenated convolutional codes and repeat-accumulate codes. Iterative turbo decoding methods have also been applied ...
The feedback capacity is known as a closed-form expression only for several examples such as the trapdoor channel, [14] Ising channel, [15] [16]. For some other channels, it is characterized through constant-size optimization problems such as the binary erasure channel with a no-consecutive-ones input constraint [17], NOST channel [18].