Search results
Results From The WOW.Com Content Network
The pocket algorithm then returns the solution in the pocket, rather than the last solution. It can be used also for non-separable data sets, where the aim is to find a perceptron with a small number of misclassifications. However, these solutions appear purely stochastically and hence the pocket algorithm neither approaches them gradually in ...
[48] [2] Matrix is an open communications protocol that includes Olm, a library that provides optional end-to-end encryption on a room-by-room basis via a Double Ratchet Algorithm implementation. [2] The developers of Wire have said that their app uses a custom implementation of the Double Ratchet Algorithm. [49] [50] [51]
The first "ratchet" is applied to the symmetric root key, the second ratchet to the asymmetric Diffie Hellman (DH) key. [1] In cryptography, the Double Ratchet Algorithm (previously referred to as the Axolotl Ratchet [2] [3]) is a key management algorithm that was developed by Trevor Perrin and Moxie Marlinspike in 2013.
English: PDF version of the Think Python Wikibook. This file was created with MediaWiki to LaTeX . The LaTeX source code is attached to the PDF file (see imprint).
The pseudocode below performs the GS algorithm to obtain a phase distribution for the plane "Source", such that its Fourier transform would have the amplitude distribution of the plane "Target". The Gerchberg-Saxton algorithm is one of the most prevalent methods used to create computer-generated holograms .
Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Donate
The resulting algorithm was called MUSIC (MUltiple SIgnal Classification) and has been widely studied. In a detailed evaluation based on thousands of simulations, the Massachusetts Institute of Technology's Lincoln Laboratory concluded in 1998 that, among currently accepted high-resolution algorithms, MUSIC was the most promising and a leading ...
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...