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nonnegative-matrix-factorization
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A new algorithm for multimodal soft coupling
, Article 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017, 21 February 2017 through 23 February 2017 ; Volume 10169 LNCS , 2017 , Pages 162-171 ; 03029743 (ISSN); 9783319535463 (ISBN) ; Babaie Zadeh, M ; Rivet, B ; Jutten, C ; Sharif University of Technology
Springer Verlag
2017
Abstract
In this paper, the problem of multimodal soft coupling under the Bayesian framework when variance of probabilistic model is unknown is investigated. Similarity of shared factors resulted from Nonnegative Matrix Factorization (NMF) of multimodal data sets is controlled in a soft manner by using a probabilistic model. In previous works, it is supposed that the probabilistic model and its parameters are known. However, this assumption does not always hold. In this paper it is supposed that the probabilistic model is already known but its variance is unknown. So the proposed algorithm estimates the variance of the probabilistic model along with the other parameters during the factorization...
Orthogonal nonnegative matrix factorization problems for clustering: A new formulation and a competitive algorithm
, Article Annals of Operations Research ; 2022 ; 02545330 (ISSN) ; Mahdavi Amiri, N ; Sharif University of Technology
Springer
2022
Abstract
Orthogonal Nonnegative Matrix Factorization (ONMF) with orthogonality constraints on a matrix has been found to provide better clustering results over existing clustering problems. Because of the orthogonality constraint, this optimization problem is difficult to solve. Many of the existing constraint-preserving methods deal directly with the constraints using different techniques such as matrix decomposition or computing exponential matrices. Here, we propose an alternative formulation of the ONMF problem which converts the orthogonality constraints into non-convex constraints. To handle the non-convex constraints, a penalty function is applied. The penalized problem is a smooth nonlinear...
Using non-negative matrix factorization for removing show-through
, Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 27 September 2010 through 30 September 2010 ; Volume 6365 LNCS , September , 2010 , Pages 482-489 ; 03029743 (ISSN) ; 9783642159947 (ISBN) ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
2010
Abstract
Scanning process usually degrades digital documents due to the contents of the backside of the scanned manuscript. This is often because of the show-through effect, i.e. the backside image that interferes with the main front side picture mainly due to the intrinsic transparency of the paper used for printing or writing. In this paper, we first use one of Non-negative Matrix Factorization (NMF) methods for canceling show-through phenomenon. Then, non-linearity of show-through effect is included by changing the cost function used in this method. Simulation results show that this proposed algorithm can remove show-through effectively
Two multimodal approaches for single microphone source separation
, Article European Signal Processing Conference, 28 August 2016 through 2 September 2016 ; Volume 2016-November , 2016 , Pages 110-114 ; 22195491 (ISSN ; 9780992862657 (ISBN) ; Babaie Zadeh, M ; Rivet, B ; Jutten, C ; Sharif University of Technology
European Signal Processing Conference, EUSIPCO
2016
Abstract
In this paper, the problem of single microphone source separation via Nonnegative Matrix Factorization (NMF) by exploiting video information is addressed. Respective audio and video modalities coming from a single human speech usually have similar time changes. It means that changes in one of them usually corresponds to changes in the other one. So it is expected that activation coefficient matrices of their NMF decomposition are similar. Based on this similarity, in this paper the activation coefficient matrix of the video modality is used as an initialization for audio source separation via NMF. In addition, the mentioned similarity is used for post-processing and for clustering the rows...
Multimodal soft nonnegative matrix go-factorization for convolutive source separation
, Article IEEE Transactions on Signal Processing ; Volume 65, Issue 12 , 2017 , Pages 3179-3190 ; 1053587X (ISSN) ; Babaie Zadeh, M ; Rivet, B ; Jutten, C ; Sharif University of Technology
Abstract
In this paper, the problem of convolutive source separation via multimodal soft Nonnegative Matrix Co-Factorization (NMCF) is addressed. Different aspects of a phenomenon may be recorded by sensors of different types (e.g., audio and video of human speech), and each of these recorded signals is called a modality. Since the underlying phenomenon of the modalities is the same, they have some similarities. Especially, they usually have similar time changes. It means that changes in one of them usually correspond to changes in the other one. So their active or inactive periods are usually similar. Assuming this similarity, it is expected that the activation coefficient matrices of their...
Design and Analysis of Optimization Algorithms for Solving Nonlinear Optimization Pproblems with Orthogonal Constraints and Certain Applications
, Ph.D. Dissertation Sharif University of Technology ; Mahdavi Amiri, Nezamoddin (Supervisor)
Abstract
Orthogonal Nonnegative Matrix Factorization (ONMF) with orthogonality constraints on a matrix has been found to provide better clustering results over existing clustering problems . Because of the orthogonality constraint , this optimization problem is difficult to solve . Many of the existing constraint-preserving methods deal directly with the constraints using different techniques such as matrix decomposition or computing exponential matrices . Here , we propose an alternative formulation of the ONMF problem which converts the orthogonality constraints into non-convex constraints . To handle the non-convex constraints , a penalty function is applied . The penalized problem is a...
A projected gradient-based algorithm to unmix hyperspectral data
, Article European Signal Processing Conference ; 2012 , Pages 2482-2486 ; 22195491 (ISSN) ; 9781467310680 (ISBN) ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
2012
Abstract
This paper presents a method to solve hyperspectral unmixing problem based on the well-known linear mixing model. Hyperspectral unmixing is to decompose observed spectrum of a mixed pixel into its constituent spectra and a set of corresponding abundances. We use Nonnegative Matrix Factorization (NMF) to solve the problem in a single step. The proposed method is based on a projected gradient NMF algorithm. Moreover, we modify the NMF algorithm by adding a penalty term to include also the statistical independence of abundances. At the end, the performance of the method is compared to two other algorithms using both real and synthetic data. In these experiments, the algorithm shows interesting...
Muscle synergies based on a biomechanical biaxial isometric shoulder model minimizing fatigue
, Article ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis, ESDA2010, 12 July 2010 through 14 July 2010 ; Volume 1 , 2010 , Pages 797-804 ; 9780791849156 (ISBN) ; Aminian, K ; Asghari, M ; Parnianpour, M ; Sharif University of Technology
Abstract
In this study we utilize the concept of synergy formation as a simplifying control strategy to manage the high number of degrees of freedom presented in the maintenance of the posture of the shoulder joint. We address how to find the muscle synergy recruitment map to the biomechanical demands (biaxial external torque) during an isometric shoulder task. We use a numerical optimization based shoulder model to obtain muscle activation levels when a biaxial external isometric torque is exposed at the shoulder glenohumeral joint. In the numerical simulations, different shoulder torque vectors parallel to the horizontal plane are considered. For each selected direction for the torque, the...
Image annotation using multi-view non-negative matrix factorization with different number of basis vectors
, Article Journal of Visual Communication and Image Representation ; Volume 46 , 2017 , Pages 1-12 ; 10473203 (ISSN) ; Jamzad, M ; Sharif University of Technology
Academic Press Inc
2017
Abstract
Automatic Image Annotation (AIA) helps image retrieval systems by predicting tags for images. In this paper, we propose an AIA system using Non-negative Matrix Factorization (NMF) framework. The NMF framework discovers a latent space, by factorizing data into a set of non-negative basis and coefficients. To model the images, multiple features are extracted, each one represents images from a specific view. We use multi-view graph regularization NMF and allow NMF to choose a different number of basis vectors for each view. For tag prediction, each test image is mapped onto the multiple latent spaces. The distances of images in these spaces are used to form a unified distance matrix. The...
A multi-view-group non-negative matrix factorization approach for automatic image annotation
, Article Multimedia Tools and Applications ; Volume 77, Issue 13 , 2018 , Pages 17109-17129 ; 13807501 (ISSN) ; Jamzad, M ; Sharif University of Technology
Springer New York LLC
2018
Abstract
In automatic image annotation (AIA) different features describe images from different aspects or views. Part of information embedded in some views is common for all views, while other parts are individual and specific. In this paper, we present the Mvg-NMF approach, a multi-view-group non-negative matrix factorization (NMF) method for an AIA system which considers both common and individual factors. The NMF framework discovers a latent space by decomposing data into a set of non-negative basis vectors and coefficients. The views divided into homogeneous groups and latent spaces are extracted for each group. After mapping the test images into these spaces, a unified distance matrix is...
Shared and specific synchronous muscle synergies arisen from optimal feedback control theory
, Article 2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09, Antalya, 29 April 2009 through 2 May 2009 ; 2009 , Pages 155-158 ; 9781424420735 (ISBN) ; Vahdat, S ; Vosoughi Vahdat, B ; National Institutes of Health, NIH; National Institute of Neurological Disorders and Stroke, NINDS; National Science Foundation, NSF ; Sharif University of Technology
2009
Abstract
In this study the properties of muscle synergies, arising from optimal feedback control are investigated. Three different tasks namely reaching, via-point, and hitting are performed using optimization of corresponding cost functions. Then by applying non-negative matrix factorization method to a dataset of muscle tensions, synchronous muscle synergies are obtained. In this way, different muscle patterns can be generated by linear combination of these basis vectors with non-negative time-varying scaling coefficients. According to our simulations some of obtained muscle synergies are shared between tasks and some of them are specific for one task. This finding is also in agreement with the...
Is there a reliable and invariant set of muscle synergy during isometric biaxial trunk exertion in the sagittal and transverse planes by healthy subjects?
, Article Journal of Biomechanics ; Volume 48, Issue 12 , Sep , 2015 , Pages 3234-3241 ; 00219290 (ISSN) ; Mousavi, S. J ; Hadizadeh, M ; Narimani, R ; Khalaf, K ; Campbell Kyureghyan, N ; Parnianpour, M ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
It has been suggested that the central nervous system simplifies muscle control through basic units, called synergies. In this study, we have developed a novel target-matching protocol and used non-negative matrix factorization (NMF) technique to extract trunk muscle synergies and corresponding torque synergies. Isometric torque data at the L5/S1 level and electromyographic patterns of twelve abdominal and back muscles from twelve healthy participants (five females) were simultaneously recorded. Each participant performed a total number of 24 isometric target-matching tasks using 12 different angular directions and 2 levels of uniaxial and biaxial exertions. Within- and between-subject...
The association between motor modules and movement primitives of gait: A muscle and kinematic synergy study
, Article Journal of Biomechanics ; Volume 134 , 2022 ; 00219290 (ISSN) ; Karami, H ; Baniasad, M ; Shojaeefard, M ; Farahmand, F ; Sharif University of Technology
Elsevier Ltd
2022
Abstract
In spite of the extensive literature on the analysis of the muscle synergies during gait, the functionality of these synergies has not been studied in detail. This study explored the relationship between the motor modules and the kinematic maneuvers involved in human walking. Motion and surface electromyography data (of 28 trunk and lower extremity muscles) were acquired from ten healthy subjects during ten trials of self-selected speed gait each. The joint angle trajectories were half-wave rectified and divided into two independent positive directional degrees-of-freedom. The muscle and kinematic synergies were both extracted using the non-negative matrix factorization (NNMF) technique and...