search: wavelet

ThinkGeo.Ecw

** The classes in this package have been replaced by those in ThinkGeo.Gdal. ** ThinkGeo.Ecw works with both .NET Core(3.0 and above) and .NET Framework(4.6.2 and above). It is a layer extension to the ThinkGeo product line that provides the ability to render an Ecw file on a map. ECW is a wavelet image compression system developed by ER Mapper. It allows you to combine and compress large sets of satellite images into a single file. The images can be accessed very quickly at a variety of scales. ** This is an extension for use in ThinkGeo's product line, and cannot be used standalone. See below for more details. ** Docs and Product Guides: https://docs.thinkgeo.com/ API Documentation: https://wiki.thinkgeo.com/wiki/12.0/thinkgeo.core ThinkGeo Cloud APIs: https://cloud.thinkgeo.com This is a commercial product with a free 30-day evaluation. Start your evaluation by signing up at https://helpdesk.thinkgeo.com/register and downloading the ProductCenter application. Supported Platforms: Windows, Linux - ThinkGeo UI Components based on .NET Core - ThinkGeo UI for Android. ThinkGeo UI for iOS. ThinkGeo UI for Blazor. ThinkGeo UI for WebApi. ThinkGeo UI for WPF.

v14.2.1

↙ 684.3K / total

SpatialGISThinkGeoECWRaster

CenterSpace.NMath.Standard.Windows.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires Visual Studio 2015-2019 C++ x64 runtime. Requires x64 hardware.

v7.4.2.16

↙ 953.9K / total

mathstatisticsnumericsprobabilitylinear

pkg

AppliedAlgebra.WaveletCodesTools

Tools for working with Wavelet-codes

v1.2.1

↙ 3.5K / total

AppliedalgebraFinitefieldsWavelet

CenterSpace.NMath.Premium

The GPU-accelerated version of package CenterSpace.NMath. With a few minor exceptions, such as optional GPU configuration settings, the API is identical between CenterSpace.NMath.Premium and CenterSpace.NMath. If using at least .NET Framework 4.6.1 or .NET Core 2.0, we recommend using one of our NMath .NET Standard NuGet packages.

v6.2.0.58

↙ 343.5K / total

GPUmathstatisticsnumericslinear

CenterSpace.NMath.Standard.Linux.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires libgcc linux. Requires x64 hardware.

v7.4.2.16

↙ 333.5K / total

mathstatisticsnumericsprobabilitylinear

CenterSpace.NMath

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. If you're using at least .NET Framework 4.6.1 or .NET Core 2.0, we recommend using one of our NMath .NET Standard NuGet packages.

v6.2.0.58

↙ 172.2K / total

mathstatisticsnumericslinearalgebra

CenterSpace.NMath.Standard.Windows.X86.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5 or .NET Core 2.0. Does not support .NET Framework. Requires Visual Studio 2017 C++ x86 and x64 runtimes. Requires x64 hardware.

v7.1.0.47

↙ 178.4K / total

mathstatisticsnumericsprobabilitylinear

UMapx

Cross-platform .NET library for digital signal processing. Fast and optimized.

v7.5.1.5

↙ 120.1K / total

imagevideosignalprocessinganalytics

CenterSpace.NMath.Standard.WindowsAndLinux.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires x64 hardware. On Windows, requires Visual Studio 2017 C++ x64 runtime. On Linux, requires libgcc.

v7.1.0.47

↙ 142.7K / total

mathstatisticsnumericsprobabilitylinear

pkg

BelNytheraSeiche.WaveletMatrix

A .NET library providing a high-performance Wavelet Matrix, Suffix Array, FM-Index, LCP Index and Burrows Wheeler Transform. Core Data Structures: - Wavelet Matrix: Generic implementation supporting various data types with efficient Rank, Select, Quant - Sparse Table: For fast Range Minimum Queries (RMQ) on static arrays. Text Analysis Components: - Suffix Array: The foundational class for most text analysis. It builds a Suffix Array and LCP Array from a given text, enabling fast substring searches. - LCP Index: Provides O(1) LCP queries between any two suffixes using a Sparse Table. - FM-Index: A full-text index based on the Burrows-Wheeler Transform, allowing efficient substring search operations (Count/Locate). Ideal for applications in bioinformatics, text processing, and data compression. For more details, please visit the project repository on GitHub.

v1.0.6

↙ 1.2K / total

stringologydata-structureswavelet-matrixsuffix-arraysa-is

CenterSpace.NMath.Standard.OSX.X64

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires x64 hardware.

v7.2.0.35

↙ 105.9K / total

mathstatisticsnumericsprobabilitylinear

CenterSpace.NMath.Standard.Windows.X86

Foundational classes for financial, engineering, and scientific applications, including complex number classes, general vector and matrix classes, structured sparse matrix classes and factorizations, general sparse matrix classes and factorizations, general matrix decompositions, least squares solutions, random number generators, Fast Fourier Transforms (FFTs), numerical integration and differentiation methods, function minimization, curve fitting, root-finding, linear and nonlinear programming. This package also provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization. Built on .NET Standard 2.0. Requires a minimum of .NET Standard 2.0, .NET 5, .NET Core 2.0 or .NET Framework 4.6.1. Requires Visual Studio 2017 C++ x86 runtime.

v7.1.0.47

↙ 41.8K / total

mathstatisticsnumericsprobabilitylinear

pkg

Neuronic.TimeFrequency

Feature extraction library specialized in Time-Frequency domain features. Includes Wavelet transforms, spectrograms, time-frequency distributions and other algorithms.

v1.5.0

↙ 2.0K / total

waveletCWTTFDCWDEMD

BioFSharp.ImgP

Image recognition and analysis using wavelet transformations

v1.2.0

↙ 7.7K / total

F#FSharpbioinformaticsbiostatisticsdatascience

Leadtools.Jpeg2000✓

Supported Platforms: • NETStandard • UWP • XamariniOS • XamarinAndroid • NETFramework Load, convert, and save JPEG 2000 files and code streams as well as utilize advanced JPEG 2000 Part 6 (JPM) features. LEADTOOLS JPEG 2000 compression/decompression conforms to the JPEG 2000 International Standard. This state-of-the-art ISO/ITU still image compression provides a fast and flexible solution for high-quality, wavelet-based compression. LEAD is fully committed to support all future parts as they are released. Therefore, LEADTOOLS JPEG 2000 support will continue to grow as the JPEG 2000 standard grows. This is just a small part of a large technology offering called LEADTOOLS. To see all that LEADTOOLS has to offer, go to https://www.leadtools.com Use the following link to register for a LEADTOOLS license file that is required to use this NuGet. Additionally, the link provides access to the LEADTOOLS Installer. The Installer includes 100’s of demo applications with source code to jump start your development: https://bit.ly/LEADTOOLS_NUGET

v23.0.0.5

↙ 64.4K / total

JPEG2000J2Kwavelet-compressionJPMJPEG-2000