Search Results for "signal processing"

...SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. Both SciPy and NumPy run on all popular operating systems, are fast and easy to install, and are powerful yet easy to use. ...

...A long awaited new feature is tracing client request life cycle to figure out when and why client request spends a time waiting for connection establishment, getting server response headers etc. Now it is possible by registering special signal handlers on every request processing stage. The main change is dropping yield from support and using async/await everywhere. Farewell, Python 3.4. You often want to send some sort of data in the URL’s query string. If you were constructing the URL by hand, this data would be given as key/value pairs in the URL after a question mark, e.g. httpbin.org/get?...

Pybris is a compiler written in Python using Pyparsing for the B Programming Language. The compiler emits a variant of Bitmario RISVM assembly. The practical goal of the project is to provide a way to develop digital signal processing (DSP) effects for the Competent Audio library that is a friendlier alternative to writing RISVM assembly by hand. Pybris is written for Python 2.7, but has also been tested to run with Python 3.8.10.

...The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. The base of available algorithms is steadily increasing and includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.

This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.