Search Results for "algorithm"
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Showing 35 open source projects for "algorithm"
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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Enhanced SAR Compression
VOP Algorithm with improved speed and compression
This work is described in: Orzada S, Fielder TM, Quick HH, Ladd ME, "A local SAR compression algorithm with improved compression, speed and flexibility", https://doi.org/10.1002/mrm.28739. This new algorithm is an iterative expansion of the exisisting local SAR compression algorithm for MRI proposed by Lee et al. ( https://doi.org/10.1002/mrm.23140) The number of VOPs is approximately halved with the new algorithm, while at the same time the compression time is reduced with speed-up... -
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iElectrodes
intracranial electrodes localization toolbox
iElectrodes is a free and open-source Matlab® toolbox to obtain intracranial electrode coordinates from MRI and CT images. Precise and reliable localization can be achieved fast and in a semiautomatic way with minimal user intervention. The toolbox works with ECoG (subdural grids and strips) and SEEG (depth) electrodes. The new GridFit algorithm can precisely localize high-density electrodes (up to 3mm). Brain parcellations (atlas) and surfaces can be imported to aid 2D and 3D visualization... -
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Blueprint XAS is a Matlab-based suite designed for the processing and analysis of near-edge x-ray absorption spectroscopy (XAS) data. The suite is designed primarily to assist users in exploring reasonable fit solutions while minimizing user bias.
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GRAMPC
A gradient-based augmented Lagrangian framework for embedded NMPC
GRAMPC is a nonlinear MPC framework that is suitable for dynamical systems with sampling times in the (sub)millisecond range and that allows for an efficient implementation on embedded hardware. The algorithm is based on an augmented Lagrangian formulation with a tailored gradient method for the inner minimization problem. GRAMPC is implemented in plain C with an additional interface to C++ and MATLAB/Simulink. The basic structure and usage of GRAMPC are described in the documentation... -
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Stoner-Wohlfarth hysteresis
Hysteresis of ellipsoidal single domain ferromagnetic particle.
Magnetization process of a single domain ellipsoidal particle: SW_particle. Magnetization of isotropic bulk material composed of 100 particles: SW_bulk. The details of the algorithm are described in the paper: 1. Zsolt Szabó, Amália Iványi, Computer-aided simulation of Stoner–Wohlfarth model, Journal of Magnetism and Magnetic Materials, Volumes 215–216, 2, June 2000, Pages 33-36. 2. Zsolt Szabó, Amália Iványi, Preisach Type Bulk Vector Hysteresis Model from Generalized... -
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VOP post-processing
Post-processing algorithms for SAR compression
Here we introduce to algorithms for post-processing of VOP sets. Algorithm 1 reduces the Overestimation for a given set of VOPs. Especially useful to reduce the overestimation in VOP sets calculated with the compression algorithms by Lee et al. and Orzada et al. Algorithm 2 tests a given set of VOPs for redundancy. It can be used to reduce the number of VOPs in a dataset produced by Eichfelder and Gebhardt's algorithm. Especially useful when you have a vendor provided VOP set only. -
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A2RMS Algorithm
Implementation of the A2RMS Algorithm in Matlab
Implementation of the A2RMS Algorithm for univariate densities defined for real values. -
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Relative Overestimation VOP
VOP compression for MRI with overestimation control
**** This work is outdated! For better compression and speed use these: ***** https://sourceforge.net/projects/enhanced-sar-compression/ Virtual Observation Points SAR compression. Contains multiple Algorithms: Compression according to Eichfelder et al. and Lee et al. The Lee algorithm is enhanced by including overestimation control to reduce maximum relative overestimation. All algorithms are implemented in Matlab and were optimized for enhanced speed. Needs Matlab R2016b at least... -
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LIPRAS, Line-Profile Analysis Software
Peak fitting GUI for diffraction data
LIPRAS v466 LIPRAS [LEEP-ruhs], short for Line-Profile Analysis Software, is a graphical user interface for least-squares fitting of Bragg peaks in powder diffraction data. For any region of the inputted data, user can choose which profile functions to apply to the fit, constrain profile functions, and view the resulting fit in terms of the profile functions chosen. If you use LIPRAS for your research, please cite it: Giovanni Esteves, Klarissa Ramos, Chris M. Fancher, and Jacob L.... -
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De_Lux
Deconvolution of luminescence cross-talk in microplate reader data
An algorithm to deconvolve the luminescence cross-talk in high-throughput gene expression profiling to recover the true luminescence activity of a microplate. -
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UmUTracker
A MATLAB program for 2D particle tracking or 3D DHM based tracking.
We present a versatile and fast MATLAB program (UmUTracker) that automatically detects and tracks particles by analyzing long video sequences acquired by either light microscopy or digital holography microscopy (DHM). Our program finds the 2D particle center position using an isosceles triangle transform and the axial position by a fast implementation of Rayleigh-Sommerfeld numerical reconstruction algorithm using a one dimensional radial intensity profile. *Updates v1.1: 2017/11/21- Bug... -
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The purpose of this program is to provide the user with a convenient algorithm for automatic Independent Component (IC) selection with respect to the contributions of the ICs to a certain event-related brain potential (ERP). www.jan-wessel.de
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This package includes a collection of MATLAB files which are designed to: 1. Given a calibration scan of the image of a point emitter with an engineered point spread function (PSF), 2. Perform a phase retrieval algorithm based on maximum likelihood estimation (MLE) of a phase aberration term which is added to the theoretical pupil function of the imaging system. 3. Use the phase-retrieved pupil function to perform single-emitter localization. Accompanying publication available here...
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Density-ratio based clustering
Discovering clusters with varying densities
This site provides the source code of two approaches for density-ratio based clustering, used for discovering clusters with varying densities. One approach is to modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The other approach involves rescaling the given dataset only. An existing density-based clustering algorithm, which is applied to the rescaled dataset, can find all clusters with varying... -
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mAPV
modified Asymmetric Pseudo-Voigt Model
A new peak detection algorithm for MALDI mass spectrometry data based on a modified Asymmetric Pseudo-Voigt model -
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cusAPV
customized Asymmetric Pseudo-Voigt Model
A new peak detection algorithm for MALDI mass spectrometry data based on a customized Asymmetric Pseudo-Voigt model -
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Fingerprint Recognition System
Fingerprint Recognition System 5.3 - Matlab source code
The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state... -
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Face Recognition System
Face Recognition System Matlab source code
Research on automatic face recognition in images has rapidly developed into several inter-related lines, and this research has both lead to and been driven by a disparate and expanding set of commercial applications. The large number of research activities is evident in the growing number of scientific communications published on subjects related to face processing and recognition. Index Terms: face, recognition, eigenfaces, eigenvalues, eigenvectors, Karhunen-Loeve algorithm. -
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Cell decomposition is one of the first applicable solution for path planning - robot path planning. The algorithm aims to find free areas (cells not occupied by obstacles) in the configuration space, and build a graph of adjacency for these cells.
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LWPR
Locally Weighted Projection Regression (LWPR)
Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu Vijayakumar... -
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MIT SPHERES Simulation (Release)
MIT's spacecraft simulator for control algorithm development
The SPHERES simulation is designed to support most software-related aspects of single- and multi-satellite SPHERES operations. The simulation code base consists of simulated versions of most of the SPHERES core flight code and additional code that simulates dynamics, communications, and other environmental interaction. The simulation is particularly valuable during the early stages of algorithm development and implementation as an aid in accelerating the learning curve for any Guest... -
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LAVA for AFM
Lloyd's Algorithm-based Volumetric Analysis for AFM Images
This MATLAB-based program enables analysis of AFM images. In particular, it allows the user to measure the volume of all distinguishable features in an image and to isolate and sort those particles. As the name implies, LAVA uses Lloyd's Algorithm, also known as k-means sorting, to identify a small set of volumes representative of the actual distribution of particle in the image. Although developed for determining feature volume, LAVA is also completely compatible with other types of image... -
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lonestar
A feature selection and classification algorithm based on L1 Norm SVM
A feature selection and classification algorithm. It is based on L1 Norm Support Vector Machine with t-test and Recursive Feature Elimination.
