22 skills found
MVRonkin / DsatoolsDigital signal analysis library for python. The library includes such methods of the signal analysis, signal processing and signal parameter estimation as ARMA-based techniques; subspace-based techniques; matrix-pencil-based methods; singular-spectrum analysis (SSA); dynamic-mode decomposition (DMD); empirical mode decomposition; variational mode decomposition (EMD); empirical wavelet transform (EWT); Hilbert vibration decomposition (HVD) and many others.
Cydhra / VersSuccinct data structures using very efficient rank and select
math-hiyoko / Wavelet Matrixwavelet-matrix library for Python
mahdieslaminet / AI Based Breast Canser DetectionDesign and implementation of filter bank and Feature matrix of mammography images in order to integrate wavelet transform with artificial neural network in breast cancer diagnosis
MitI-7 / WaveletMatriximplementation of dynamic wavelet matrix(tree) and static wavelet matrix
kurpicz / PwmParallel Wavelet Tree and Wavelet Matrix Construction
ikegami-yukino / Shellinford PythonWavelet Matrix/Tree succinct data structure for full text search (based on shellinford C++ library)
sekineh / Wavelet Matrix RsWavelet Matrix implementation written in Rust
jcdemunck5 / DMS ProjectsThese C/C++ source files consist of 150 classes, 300,000 lines of code, excluding a Qt-based user interface. Its functionality includes: GLM-statistics, hierarchical clustering, (non)-linear optimization, L1 and L2 norm minimization, Hungarian algorithm, EEG/MEG forward and inverse modelling, Boundary Element Method, spatio/temporal covariance modelling, image fusion, triangular meshes, KD-trees, topological error correction, marching cubes & spherical triangulations, sparse matrices and matrix operations, spherical harmonics, wavelets, spectra and spectrograms, Fast Fourier transform (FFTWest), data import for many different EEG/MEG data formats, data import for many image data formats.
hideo55 / Cpp HSDSSuccinct Data Structure Library Collection.Includes bit-vector/wavelet-matrix/trie.
sypdbhee / DWPT NMFApplying discrete wavelet packet transform (DWPT) and nonnegative matrix factorization (NMF) analysis to speech enhancement tasks. Conventional speech enhancement system structure was performed to DWPT-NMF. Please referenced to "S. S. Wang et al., "Wavelet Speech Enhancement Based on Nonnegative Matrix Factorization," in IEEE Signal Processing Letters, vol. 23, no. 8, pp. 1101-1105, Aug. 2016."
BioJulia / WaveletMatrices.jlThe Wavelet Matrix
Rakshana96 / An Enhancement In Detection Of Brain Tumor Through Image Fusion And ANN Medical image fusion is the process of combining two different modality images into a single image. The resultant image can help the physicians to extract features that may not be easily identifiable in an individual modality images. This paper aims to demonstrate an efficient method for detection of brain tumor from CT and MRI images of the brain, by applying image fusion, segmentation, feature extraction and classification. Initially, the source images are decomposed into low-level sub-band and high level sub-band by Discrete Wavelet Transform (DWT). The fused low level sub-band and high level sub-band are reconstructed to form the final fused image using Inverse Discrete Wavelet Transform (IDWT). Parameter analysis is done on the fused image. The fused image is then segmented using Otsu’s thresholding operation and the texture features are extracted forms the Grey Level Co-occurrence Matrix (GLCM) technique. Finally, the extracted feature is provided to Adaptive Neural Network (ANN) classifier to identify and predict the nature of the tumor. Further this proposed method gives an accuracy of 93.5% for 12 samples of MRI and CT images each.
risilab / Learnable MMFLearning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs
Weenkus / FM IndexA FM index implementation in C made by Zoran Krišto and Vinko Kodžoman. The index supports 3 versions of the FM index by using the different method for rank queries (Matrix, Wavelet Tree 8 byte code, Wavelet Tree bit code). The Suffix Array is constructed by using the libdivsufsort library.
hideo55 / Go WaveletmatrixThe implementation of Wavelet-Matrix in Go.
hiroshi-manabe / Wavelet Matrix CppA test implementation of Wavelet Matrix based on wat-array by Daisuke Okanohara.
frknrnn / Covid19 Classification TmemprMedical images are crucial data sources for not easily diagnosed diseases. X-rays, one of the medical images, have high resolution. Processing high-resolution images leads to a few problems such as the difficulties in data storage, the computational load, and the time required to process high-dimensional data. It is a vital element to be able to diagnose diseases fast and accurately. In this study, a data set consisting of lung X-rays of patients with and without COVID-19 symptoms was taken into consideration and disease diagnosis from these images can be summarized in 2 steps as preprocessing and classification. Preprocessing step is the feature extraction process and in this step, the recently developed decomposition-based method Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) is proposed as a feature extraction method. Classification of images is the second step where the Random Forest and Support Vector Machine (SVM) is applied as classifiers. Also, X-ray images have been reduced by 99,9\% with TMEMPR and with several state-of-the-art feature extraction methods which are Discrete Wavelet Transform (DWT), Discrete Cosine Transform(DCT) The results are examined under different feature extraction methods. It is observed that a higher accuracy rate of classification is achieved by using the TMEMPR method.
shibukawa / Wavelet Matrix.jsxWaveletMatrix implementation for JS/JSX/AMD/CommonJS
George-wu509 / Wavelet MS Quantificatio MethodA novel and concise algorithm for MS data peak detection and especially peak quantification by utilize 2-D Continuous Wavelet Transform (CWT) coefficients matrix information, which derived from applying CWT over MS raw data. No further baseline removal or peak smoothing preprocessing steps are required before peak detection.
