Search Results for "signal processing" - Page 5
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Showing 192 open source projects for "signal processing"
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TONIC
Analysis of neural spiking data generated by multi-electrode arrays
A neuroscience data analysis package for handling extracellular potentials recorded by multi-electrode arrays, including signal processing, event detection, feature extraction, and spike sorting. -
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Swift AI
The Swift machine learning library
...The example projects are another great resource for seeing real-world usage of these tools. Swift AI currently depends on Apple's Accelerate framework for vector/matrix calculations and digital signal processing. -
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GTK+ IOStream
GTK+iostream, Data plots, ORB, Neural Networks, WSOLA
...You can also plot like so : Plot figure; figure.plot(x, y, x.size()); Plotting utilises GtkDataBox.sf.net ORB utilises www.zeroc.com Feed forward neural networks with different activation functions. Audio playback/recording and digital signal processing (DSP) - utilising Jack www.jackaudio.org -
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Gimias
Graphical Interface for Medical Image Analysis and Simulation
GIMIAS is a workflow-oriented environment for solving advanced biomedical image computing and individualized simulation problems, which is extensible through the development of problem-specific plug-ins. In addition, GIMIAS provides an open source framework for efficient development of research and clinical software prototypes integrating contributions from the Physiome community while allowing business-friendly technology transfer and commercial product development. -
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...Cas-OFFinder is an ultrafast and highly versatile off-target searching tool. Importantly, Cas-OFFinder is written in OpenCL, enabling operation in diverse platforms such as central processing units (CPUs), graphics pro-cessing units (GPUs), digital signal processors (DSPs), and other processors. Cas-OFFinder runs on Windows and POSIX (portable operating system interface) platforms.
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The MusicKit & SndKit is an object-oriented software system for building music, sound, signal processing & MIDI applications. The distribution is a comprehensive package that includes on-line documentation, code examples, utilities, applications & scores
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...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.
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deconvolv
deconvolv: convolution and deconvolution of WAV files
deconvolv: convolution and deconvolution of WAV files Supported signal processing functions: correlation, convolution, de-convolution, convolution with Hilbert transformation, de-convolution with Hilbert transformation Copyright (c) 2008-2016 by Klaus Michael Indlekofer. All rights reserved. Note: Special restrictions apply. See disclaimers below and within the distribution. (We are not affiliated in any way with companies/persons mentioned above. -
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AhoTTS Iparrahotsa
TTS for Basque Lapurdian dialect
AhoTTS Iparrahotsa is the TTS developed at the Aholab Signal Processing Laboratory of the University of the Basque Country (UPV/EHU) for the Lapurdian dialect of Basque. This dialect is spoken at the Northern area of the Basque speaking area (French region). This project was funded by the Euroregion Aquitaine-Euskadi under grant EUSKADI-2012-004. -
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0sex
Zero Simulation EXperiment - simulation framework experiment
The main goal of the project is to explore different techniques and approaches related to general communicating processes, simulation, distributed processing, game "world simulation", dynamic signal processing etc. -
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...for cite İlhan Umut, PSGMiner: A modular software for polysomnographic analysis, Computers in Biology and Medicine, Volume 73, 1 June 2016, Pages 1-9, ISSN 0010-4825, http://dx.doi.org/10.1016/j.compbiomed.2016.03.023. (//www.sciencedirect.com/science/article/pii/S0010482516300750) Keywords: Computer software; Digital signal processing; Machine learning; Polysomnography APPLICATIONS Medicine: diagnosis (neurophysiology, sleep disorders tests…) Research: biomedical engineering, signal processing and machine learning Educational
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KMBOX - Kernel Methods Toolbox
A collection of kernel-based algorithms for Matlab.
KMBOX is a collection of MATLAB programs that implement kernel-based algorithms, with a focus on regression algorithms and online algorithms. It can be used for nonlinear signal processing and machine learning. -
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Software for speech research. It includes programs and libraries for signal processing, along with general purpose scientific libraries. Most of the code is in Python, with C/C++ supporting code. Also, contains code releases corresponding to publishe
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Timbre Imitation and Adaptation
Timbre Imitation and Adaptation for Experimental Music Instruments
Timbre Imitation and Adaptation for Experimental Music Instruments: An Interactive Approach Using Real-Time Digital Signal Processing Framework Mingfeng Zhang Dept. of Electrical and Computer Engineering, University of Rochester We present a real-time digital signal processing toolbox to extend the timbre control capability of experimental musical instruments. This toolbox is written in C for Texas instrument OMAP-L138 DSP + ARMS9 Development Kit (TMDXLCDK138) and TI/ Digital Spectrum XDS100 14 Pin JTAG Emulator (TMDSEMU100V2U-14T) The readme file in the zip file has more details More details can be found in this paper: Mingfeng Zhang, John Granzow, Gang Ren, and Mark Bocko, “Timbre Imitation and Adaptation for Experimental Music Instruments: An Interactive Approach Using Real-Time Digital Signal Processing Framework”, Proceedings of the Audio Engineering Society (AES) 137th Convention, pp. 1- 8,Los Angeles, CA, Oct. 9-12, 2014. -
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Sample Level Musical Timeline
Sample Level Modulation of Musical Timeline
Sample Level Modulation of Musical Timeline Mingfeng Zhang Dept. of Electrical and Computer Engineering, University of Rochester In this toolbox we provide signal processing tools to allocate music events (samples of musical notes) to specified time locations with sample level accuracy. In this implementation, we use computational tools to add in micro-timing variations in J.S. Bach four-part chorales as a "visualizer" for big data. By extracting data patterns from multiple time scales, we implement a tool that musicians can perform the big data at different resolutions. ... -
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Vibrato Toolbox
Vibrato Toolbox: Parametric Analysis of Musical Vibrato
Vibrato Toolbox: Parametric Analysis of Musical Vibrato from High-Precision Magnitude/Frequency Tracking Mingfeng Zhang ECE, Univ. of Rochester Part I Analysis of individual music tones This MATLAB toolbox provides signal analysis tools for time-frequency analysis and for parametric analysis of musical vibrato Part II Analysis of multiple music tones or multiple harmonic partials This toolbox allows you to explore a group of audio files, and obtains its related parameters... -
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Single-Trial Feature Detection in ERPs
Automatic detection of Even-Releated Potentials
This algorithm automates the process of detecting N1, N2 and P2 features (peaks amplitude and latency) in ERPs. This is achived by a basic processing of the signal using Single-Trial EEG's derivative to find the possible peaks and then a fuzzy logic process to clasify them. -
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ApproxAdderLib
Library of Approximate Adders
...To the best of our knowledge, this is the first open-source library of approximate adders that facilitates reproducible comparisons and further research and development in this direction across various layers of design abstraction. This work is a result of collaborative effort between Chair for Embedded Systems (CES) at Karlsruhe Institute of Technology (KIT), Germany and Vision Image and Signal Processing (VISpro) Lab at SEECS-NUST, Pakistan. -
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JAMin is the JACK Audio Connection Kit (JACK) Audio Mastering interface. JAMin is designed to perform professional audio mastering of stereo input streams from JACK enabled applications. It uses LADSPA for digital signal processing (DSP).
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jmathstudio - Java Image/Signal toolkit
Java toolkit for discrete Image and Signal processing.
JMathStudio is a Java based digital image and signal processing toolkit/library. It is simple to use, portable, light (~300 Kb), extendable and free. Full source code available at https://github.com/bhavyaajani/jmathstudio Android compatible JMathStudio is available @ https://sourceforge.net/projects/jmathstudio-android/ -
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Marsyas (Music Analysis, Retrieval and Synthesis for Audio Signals) is a framework for developing systems for audio processing. It provides an general architecture for connecting audio, soundfiles, signal processing blocks and machine learning. Source code at SF is outdated! Marsyas is now hosted at GitHub: https://github.com/marsyas/marsyas Downloads are now provided at Bintray: https://bintray.com/marsyas
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A programmable signal generator and RF synthesizer for scientific experiments, especially quantum computing and quantum information processing. It includes hardware, firmware, software, and documentation, all under an open source license.
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METAlab GTG
Matlab toolbox to run a GLM on graph theoretic properties in MRI data
...Significance is determined via non-parametric permutation tests. The toolbox allows testing of both fully connected and thresholded networks (based on a range of thresholds). The toolbox also provides a data processing path for resting state fMRI data. Several options for partialing nuisance signals are available, including local and total white matter signal (Jo et al., 2013), calculation of Saad et al. (2013)'s GCOR, and the use of Chen et al. (2012) GNI method to determine whether global signal partialing is needed. In addition, Power et al. (2014)'s motion scrubbing method is available. -
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Kernel Adaptive Filtering Toolbox
a Matlab benchmarking toolbox for kernel adaptive filtering
...If you use this toolbox in your research please cite: @inproceedings{vanvaerenbergh2013comparative, author = {Van Vaerenbergh, Steven and Santamar{\'i}a, Ignacio}, booktitle = {2013 IEEE Digital Signal Processing (DSP) Workshop and IEEE Signal Processing Education (SPE)}, title = {A Comparative Study of Kernel Adaptive Filtering Algorithms}, year = {2013}, note = {Software available at \url{https://github.com/steven2358/kafbox/}} } -
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TDSApplication
A little helpful application for digital signal processing learning.
This software enables you to learn the basics of digital signal processing like additions, convolutions, delays, etc. both in time domain and frequency domain. The process of learning is carried on in a graphical environment that makes easy the process of operation construction and calculation. This software is available both in standalone application and applet form. Please, contact with project admins if you are interested in the development of the project, you will be welcome.
