./nugetz

#linear-algebra

14 packages tagged with “linear-algebra

Dew.Math

Dew.Math is the Windows-optimized high-performance numerical computation library for .NET. It provides a vectorized matrix and vector math environment with native runtime acceleration, multithreaded execution, and extensive algorithm libraries for scientific, engineering, financial, AI/ML and signal processing workloads. Core Numerical Capabilities: - Dense linear algebra (BLAS, LAPACK): SVD, QR, LQ, LU, eigenvalue problems, least-squares, rank reveals - Sparse matrix support: direct solvers (Pardiso, UMFPACK), iterative solvers (CG, BiCG, GMRES), preconditioning strategies, structured sparse formats - Complex number computation with fully vectorized math operations - Polynomial arithmetic, interpolation, splines, rational approximations, Chebyshev basis transforms - Numerical differentiation, root solving, non-linear systems, ODE support for stiff and non-stiff cases - Probability distributions (over 30 families), random number generators, Monte Carlo methods - Special mathematical functions (Airy, Bessel, Gamma-related, elliptic integrals, Legendre, etc.) Optimization and Modeling: - Non-linear curve fitting with Levenberg-Marquardt and trust-region refinements - Direct and constrained optimization (Simplex/Nelder–Mead, BFGS, Conjugate Gradient, LP, dual-phase simplex, Gomory cutting plane) - Vectorized expression parser for dynamic formula construction and symbolic-style evaluation Performance Architecture: - Native accelerated BLAS/LAPACK kernels with automatic CPU dispatch (AVX, AVX2, AVX-512) - Scalable multithreading with a lock-free memory allocator for low-GC overhead - Optional OpenCL GPU offloading for supported device targets Platform Model: - Contains Windows native acceleration binaries - For Linux native acceleration use: Dew.Math.Linux - For a pure managed, portable edition use: Dew.Math.Core Use Dew.Math when you require **maximum numerical performance on Windows** for HPC, simulation, economic modeling, data analytics, or scientific visualization workflows.

v6.3.1054.8K
dotnetcsharpwindowslinuxmacos

Dew.Math.Core

Dew.Math.Core is the portable, pure managed edition of the Dew.Math library. It provides the same high-level matrix and vector programming model, expression parser, probability and optimization toolkit, and special function support without linking to any native runtime components. This enables maximum compatibility across platforms and runtime environments. Core Numerical Capabilities (Managed): - Dense matrix and vector operations with operator overloading and method-based APIs - QR, LU, SVD and eigenvalue routines using high-quality managed linear algebra kernels - Complex number and real-valued computation with full vectorization in managed code - Sparse matrix representations with iterative solver support - Probability distributions, histogramming, random generators, Monte Carlo workflows - Nonlinear optimization, curve fitting, regression models, trust-region and gradient methods - Vectorized expression parsing for symbolic-style expression and simulation pipelines - Polynomial and spline interpolation, numerical integration and differentiation - Special function suite including Bessel, Airy, Gamma-related, Legendre and elliptic functions Portability Model: - No native libraries required (zero unmanaged dependencies) - Runs on Windows, Linux, macOS, iOS, Android, MAUI, Uno, WASM, Unity*, cloud functions and plugins - Targets netstandard2.0, net8.0, and net9.0 Use Dew.Math.Core when you need **maximum portability** in libraries, shared simulation engines, tooling, mobile deployments, WebAssembly environments, or plugin architectures.

v6.3.1014.4K
mathnumericalvectormatrixcomplex

Dew.Signal

Dew.Signal is a high-performance digital signal processing library built on top of Dew.Math, providing a comprehensive suite of optimized algorithms for real-time signal analysis, filtering, spectral estimation, modeling, and streaming signal workflows. The library is designed for scientific, engineering, audio, RF, vibration, instrumentation, control, and monitoring applications requiring both numerical accuracy and hardware-level performance on multi-core CPUs with AVX2/AVX512 support. Filter Design and Processing: - IIR filter design (Butterworth, Chebyshev I/II, Elliptic, Bessel), analog and digital domains - Order estimation, frequency transformations, bilinear and matched-Z transforms - State-space and zero-pole-numerator-domain modeling with group delay and stability analysis - FIR filter design using window methods and Remez exchange algorithm - FIR/Hilbert/differentiator/integrator design, Savitzky–Golay filtering, envelope detectors - Multi-rate filtering: half-band polyphase filters, decimation, interpolation, zoom-spectrum analysis Nonlinear and Adaptive Filters: - Sample-and-hold, sample-and-decay, and median filtering - High-quality rate conversion with 160dB stopband attenuation at high speed Spectral and Frequency-Domain Analysis: - FFT-based spectrum analyzer components with real-time UI integration support - Parametric spectral estimation: Yule–Walker, Burg, Covariance, Modified Covariance - Chirp-Z transform, bispectrum, bicoherence, transfer function, coherence estimation - Peak interpolation and peak-tracking enhancements, phase unwrapping - Real and complex cepstrum, inverse cepstrum - Spectral statistics: noise floor, SFDR, THD, THDN, SINAD, RMS, SNR measurements Signal Synthesis, Streaming, and Measurement: - Signal generators with stack-based vectorized function evaluation - Audio capture/playback with monitoring and triggering support - Data streaming and file format components for continuous acquisition and logging Forecasting and Time-Series Modeling: - Spectral forecasting based on controlled peak selection, enabling clear component-based prediction Integration and Extensions: - Works seamlessly with Dew.Math numeric structures (vectors/matrices) - Optional high-performance charting available via a separate Dew.Signal.Tee package (Windows visualization) - Part of the Dew Lab Studio ecosystem for unified math, DSP, and statistical analysis workflows Designed for reproducibility, determinism, and stable numerical behavior in long-running or real-time environments.

v6.3.105.7K
dotnetcsharpdspsignal-processingfiltering