Search Results for "signal processing"
Sort By:
Showing 243 open source projects for "signal processing"
View related business solutions-
The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
-
The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
-
1
Clock Signal
A latency-hating emulator of: the Acorn Electron, BBC Micro
Clock Signal also known as Clock Signal, is a highly sophisticated multi-system emulator designed with a strong emphasis on minimizing latency and maximizing authenticity in signal reproduction rather than relying on post-processing shortcuts. Its defining philosophy is to make emulation “invisible” to the user, meaning software can be launched directly without requiring manual configuration of machines, disks, or hardware profiles. -
2
Faust
Functional programming language for signal processing
Faust (Functional Audio Stream) is a functional programming language for sound synthesis and audio processing with a strong focus on the design of synthesizers, musical instruments, audio effects, etc. Faust targets high-performance signal processing applications and audio plug-ins for a variety of platforms and standards. The core component of Faust is its compiler. It allows to "translate" any Faust digital signal processing (DSP) specification to a wide range of non-domain specific languages such as C++, C, LLVM bit code, WebAssembly, Rust, etc. ... -
3
SigLens
100x Efficient Log Management than Splunk
Siglens is an open-source signal analysis toolkit designed for processing and visualizing time-series data, commonly used in scientific and engineering applications. -
4
AERIS-10
Open-source, low-cost 10.5 GHz PLFM phased array RADAR system
AERIS-10 appears to be a specialized signal processing and radar analysis project focused on pulse linear frequency modulation techniques, which are commonly used in modern radar systems for high-resolution detection and ranging. The project likely implements algorithms for generating, analyzing, and visualizing chirp-based radar signals, enabling experimentation with time-frequency characteristics and signal reconstruction. -
The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
-
5
SciPy
SciPy library main repository
...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. ... -
6
EEGLAB
EEGLAB is an open source signal processing environment
...It incorporates powerful tools for data import, preprocessing, independent component analysis (ICA), time-frequency analysis, artifact rejection, and visualization—all within a GUI framework that also supports scripting and plugin extensions. EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and Octave (command line only for Octave). This folder contains original Matlab functions from the EEGLAB (formerly ICA/EEG) Matlab toolbox, all released under the Gnu public license (see eeglablicence.txt). See the EEGLAB tutorial and reference paper (URLs given below) for more information. ... -
7
TorchAudio
Data manipulation and transformation for audio signal processing
...By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. The benefits of PyTorch can be seen in torchaudio through having all the computations be through PyTorch operations which makes it easy to use and feel like a natural extension. -
8
FISSURE
The RF and reverse engineering framework for everyone
...The platform supports workflows related to signal discovery, demodulation, packet inspection, fuzzing, and attack simulation, making it useful for both defensive research and controlled lab testing. Its architecture is oriented toward extensibility, so users can integrate additional hardware, signal-processing components, and protocol-specific modules depending on their needs. -
9
ArrayFire
ArrayFire, a general purpose GPU library
ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if... -
Comet Backup - Fast, Secure Backup Software for MSPsComet is a flexible backup platform, giving you total control over your backup environment and storage destinations.
-
10
DSP.jl
Filter design, periodograms, window functions
DSP.jl provides a number of common digital signal processing routines in Julia. -
11
Librosa
Python library for audio and music analysis
Librosa is a powerful Python library for analyzing and processing audio and music signals. Built on top of NumPy, SciPy, and matplotlib, it provides a wide range of tools for feature extraction, time-series manipulation, audio display, and music information retrieval. Whether you're building machine learning models for audio classification or visualizing spectrograms, Librosa is a go-to library for researchers and developers working in audio signal processing. -
12
DSPSR is a high-performance, object-oriented, digital signal processing library for radio pulsar astronomy. It implements an extensive range of algorithms and features, and can read data from most observatories, instruments, and file formats.
-
13
POT
Python Optimal Transport
This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning. -
14
Must Reading on ISAC
Must Reading Papers, Research Library, Open-Source Code
A design paradigm and corresponding enabling technologies, in which sensing and comms systems are integrated to efficiently utilize congested wireless/hardware resources, and even to pursue mutual benefits. Waveform Design and Signal Processing Aspects for Fusion of Wireless Communications and Radar Sensing. Supported by IEEE ComSoc ISAC Emerging Technology Initiative (ETI). Integrating Sensing and Communications for Ubiquitous IoT. Include reproducible codes, good papers and a research libary. -
15
pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
...It also includes utilities for visualizing audio features and analyzing patterns within sound recordings, which can be useful in applications such as speech recognition, music classification, and acoustic event detection. Because the library integrates machine learning algorithms with signal processing tools, it enables researchers to develop complete audio analysis pipelines using a single framework. -
16
WiFi DensePose
Turn WiFi signals into real-time human pose estimation and detection
WiFi DensePose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. The repository includes components for data processing, model inference, and real-time visualization, making it suitable for research and experimental deployments. ... -
17
RuView
Turn WiFi signals into real-time human sensing and spatial awareness.
...Unlike traditional vision systems, RuView operates without cameras, wearables, or cloud connectivity, making it a privacy-first sensing solution. The system runs on low-cost hardware such as ESP32 sensor meshes and performs signal processing and machine learning directly at the edge. By learning the RF signature of each environment over time, RuView adapts automatically to different spaces and improves its sensing accuracy. Designed for applications ranging from healthcare monitoring to disaster response, it enables spaces to gain spatial awareness using the radio signals already present in the environment. -
18
reverse-SynthID
Reverse engineering Gemini's SynthID detection
Reverse-SynthID is a research-focused project that analyzes and reverse-engineers Google’s SynthID watermarking system used in AI-generated images. It leverages signal processing and spectral analysis techniques to identify hidden watermark patterns without access to proprietary encoding methods. The project introduces a multi-resolution “SpectralCodebook” that maps watermark characteristics across different image sizes. Using this approach, it can detect SynthID watermarks with high accuracy and selectively reduce or remove them through frequency-domain manipulation. ... -
19
hls4ml
Machine learning on FPGAs using HLS
...The framework was originally developed for high-energy physics experiments where real-time decision systems must process large volumes of data with strict latency constraints. Over time, it has expanded to support a variety of scientific and industrial applications including signal processing, embedded systems, and biomedical monitoring. -
20
iPlug 2
C++ Audio Plug-in Framework for desktop, mobile, xr and web
iPlug 2 is a cross-platform C++ framework for developing audio plug-ins and applications that can target multiple formats and environments from a single codebase. It abstracts both the audio processing layer and the graphical user interface, allowing developers to focus on signal processing and design while the framework handles platform-specific details. The framework supports a wide range of plug-in standards, including VST, Audio Units, AAX, and newer formats like CLAP, enabling compatibility with major digital audio workstations. ... -
21
audioFlux
A library for audio and music analysis, feature extraction
A library for audio and music analysis, and feature extraction. Can be used for deep learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. audioflux is a deep learning tool library for audio and music analysis, feature extraction. It supports dozens of time-frequency analysis transformation methods and hundreds of corresponding time-domain and frequency-domain feature combinations. It can be provided to deep learning networks for training and is used to study various tasks in the audio field such as Classification, Separation, Music Information Retrieval(MIR) ASR, etc. -
22
AIOHTTP
Asynchronous HTTP client/server framework for asyncio and Python
...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?... -
23
LoopVectorization.jl
Macro(s) for vectorizing loops
...It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning. -
24
WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. WhisperJAV introduces... -
25
SFBAudioEngine
A powerhouse of audio functionality for macOS, iOS, and tvOS
SFBAudioEngine is an advanced audio engine designed for macOS and iOS, focusing on high-quality playback, precise audio control, and support for a wide range of audio formats. Built for modern Apple platforms, it provides developers with a robust tool for integrating sophisticated audio functionalities into their applications. It emphasizes extensibility, performance, and clean API design.
