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Dissertations / Theses on the topic 'Blind source separation'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Gao, Bin. "Single channel blind source separation." Thesis, University of Newcastle Upon Tyne, 2011. http://hdl.handle.net/10443/1300.

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Single channel blind source separation (SCBSS) is an intensively researched field with numerous important applications. This research sets out to investigate the separation of monaural mixed audio recordings without relying on training knowledge. This research proposes a novel method based on variable regularised sparse nonnegative matrix factorization which decomposes an information-bearing matrix into two-dimensional convolution of factor matrices that represent the spectral basis and temporal code of the sources. In this work, a variational Bayesian approach has been developed for computing

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2

Abrar, Shafayat. "Blind channel equalization and instantaneous blind source separation." Thesis, University of Liverpool, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540044.

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Latif, Mohamed Amin. "Localization of brain signal sources using blind source separation." Thesis, Cardiff University, 2006. http://orca.cf.ac.uk/54567/.

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Reliable localization of brain signal sources by using convenient, easy, and hazardless data acquisition techniques can potentially play a key role in the understanding, analysis, and tracking of brain activities for determination of physiological, pathological, and functional abnormalities. The sources can be due to normal brain activities, mental disorders, stimulation of the brain, or movement related tasks. The focus of this thesis is therefore the development of novel source localization techniques based upon EEG measurements. Independent component analysis is used in blind separation (BS

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4

Naqvi, Syed Mohsen Raza. "Multimodal methods for blind source separation of audio sources." Thesis, Loughborough University, 2009. https://dspace.lboro.ac.uk/2134/36117.

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The enhancement of the performance of frequency domain convolutive blind source separation (FDCBSS) techniques when applied to the problem of separating audio sources recorded in a room environment is the focus of this thesis. This challenging application is termed the cocktail party problem and the ultimate aim would be to build a machine which matches the ability of a human being to solve this task. Human beings exploit both their eyes and their ears in solving this task and hence they adopt a multimodal approach, i.e. they exploit both audio and video modalities. New multimodal methods for

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5

Khor, Li Chin. "Blind source separation under model misfits." Thesis, University of Newcastle upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490154.

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Blind Signal Separation (BSS) is a statistical signal processing-based technique and has recently been developed for many potential applications. This thesis aims to investigate model misfits in BSS problems as well as identify and develop efficient solutions for enhancing the performance of signal separation. This research sets out to investigate model misfits associated with finite signal sample size, mixing model, source signal and noise models. The effects of finite signal sample size on several well-known cost functions have been studied and this thesis has identified the most optimal cos

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6

Klajman, Maurice. "Mixed statistics in blind source separation." Thesis, Imperial College London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.406683.

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7

Zhou, Lihong. "Blind source separation systems for hearing aids." Thesis, University of Ottawa (Canada), 2010. http://hdl.handle.net/10393/28395.

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For many real-life situations, there is more than one speaker at a given time and people need to concentrate on a target sound signal to extract it. This process happens naturally for people with a normal hearing ability, but it is very difficult for hearing impaired persons. In this thesis, we present a system for enhancing the quality of the signal produced by a hearing aid. The proposed system combines spatial information with blind source separation (BSS) to extract the target signal. Results show that the proposed system can locate a target signal in different environments, with a good le

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8

Smith, Paul Carson. "Broadband analog opto-electronic blind source separation." Diss., Connect to online resource, 2005. http://wwwlib.umi.com/dissertations/fullcit/3178354.

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9

Badran, Salah Al-Din Ibrahim. "Efficient multiband algorithms for blind source separation." Thesis, De Montfort University, 2016. http://hdl.handle.net/2086/16089.

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The problem of blind separation refers to recovering original signals, called source signals, from the mixed signals, called observation signals, in a reverberant environment. The mixture is a function of a sequence of original speech signals mixed in a reverberant room. The objective is to separate mixed signals to obtain the original signals without degradation and without prior information of the features of the sources. The strategy used to achieve this objective is to use multiple bands that work at a lower rate, have less computational cost and a quicker convergence than the conventional

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10

Anemüller, Jörn. "Across-frequency processing in convolutive blind source separation." [S.l. : s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=962819247.

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11

Zhang, Jingyi. "Statistical blind source separation of post-nonlinear mixture." Thesis, University of Newcastle upon Tyne, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485858.

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Blind Source Separation (BSS) is a statistical signal processing technique and has recently been developed for many applications. The aim of this thesis is to investigate the blind signal separation problem under the environment where noise, reverberation and nonlinear distortion exist in the mixture and to develop novel solutions to solve the problem. The success and efficacy of the proposed algorithms is analysed in terms of robustness to noise, accuracy of recovered signal and speed of convergence. Linear BSS algorithms for instantaneous and convolutive mixtures are investigated and tested

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12

Liu, Xianhua Mechanical &amp Manufacturing Engineering Faculty of Engineering UNSW. "Blind source separation methods and their mechanical applications." Awarded by:University of New South Wales. School of Mechanical and Manufacturing Engineering, 2006. http://handle.unsw.edu.au/1959.4/24961.

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Blind Source Separation is a modern signal processing technique which recovers both the unknown sources and unknown mixing systems from only measured mixtures of signals. It has application in diverse fields such as communication, image processing, geological exploration and biomedical signal processing etc. This project studies the BSS problem, develop separation methods and reveal the potential for mechanical engineering applications. There are two models for blind source separation corresponding to the two ways that the sources are mixed, the instantaneous mixing model and the convolved mix

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13

Sansrimahachai, Puttachad. "Blind source separation algorithms for MIMO communication systems." Thesis, Imperial College London, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.419916.

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14

Addison, W. D. "Blind source separation using spatial and temporal priors." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.525254.

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15

Parathai, Phetcharat. "Blind source separation using statistical nonnegative matrix factorization." Thesis, University of Newcastle upon Tyne, 2015. http://hdl.handle.net/10443/2830.

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Blind Source Separation (BSS) attempts to automatically extract and track a signal of interest in real world scenarios with other signals present. BSS addresses the problem of recovering the original signals from an observed mixture without relying on training knowledge. This research studied three novel approaches for solving the BSS problem based on the extensions of non-negative matrix factorization model and the sparsity regularization methods. 1) A framework of amalgamating pruning and Bayesian regularized cluster nonnegative tensor factorization with Itakura-Saito divergence for separati

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16

Kervazo, Christophe. "Optimization framework for large-scale sparse blind source separation." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS354/document.

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Lors des dernières décennies, la Séparation Aveugle de Sources (BSS) est devenue un outil de premier plan pour le traitement de données multi-valuées. L’objectif de ce doctorat est cependant d’étudier les cas grande échelle, pour lesquels la plupart des algorithmes classiques obtiennent des performances dégradées. Ce document s’articule en quatre parties, traitant chacune un aspect du problème: i) l’introduction d’algorithmes robustes de BSS parcimonieuse ne nécessitant qu’un seul lancement (malgré un choix d’hyper-paramètres délicat) et fortement étayés mathématiquement; ii) la proposition d’

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17

Leong, Wai Yie. "Implementing blind source separation in signal processing and telecommunications /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe19158.pdf.

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18

Lösch, Benedikt [Verfasser]. "Complex Blind Source Separation with Audio Applications / Benedikt Lösch." München : Verlag Dr. Hut, 2013. http://d-nb.info/1042307806/34.

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19

Abadi, Bahador Makki. "New tensor factorization based approaches for blind source separation." Thesis, University of Surrey, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543925.

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E, Okwelume Gozie, and Ezeude Anayo Kingsley. "BLIND SOURCE SEPARATION USING FREQUENCY DOMAIN INDEPENDENT COMPONENT ANALYSIS." Thesis, Blekinge Tekniska Högskola, Avdelningen för signalbehandling, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1312.

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Our thesis work focuses on Frequency-domain Blind Source Separation (BSS) in which the received mixed signals are converted into the frequency domain and Independent Component Analysis (ICA) is applied to instantaneous mixtures at each frequency bin. Computational complexity is also reduced by using this method. We also investigate the famous problem associated with Frequency-Domain Blind Source Separation using ICA referred to as the Permutation and Scaling ambiguities, using methods proposed by some researchers. This is our main target in this project; to solve the permutation and scaling am

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21

Herrmann, Frank. "Independent component analysis with applications to blind source separation." Thesis, University of Liverpool, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.399147.

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22

Alphey, Marcus J. T. "Blind source separation : the effects of signal non-stationarity." Thesis, University of Edinburgh, 2002. http://hdl.handle.net/1842/11220.

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This thesis investigates the effect of non-stationarity reduction, in the form of silence removal, on the performance of blind separation and deconvolution techniques for speech signals. An information-maximisation-based system is used for the separation of instantaneously mixed signals, and a decorrelating system for convolutively mixed signals. An introduction to the concepts of adaptive signal processing, blind signal processing and artificial neural networks is presented. A review of approaches to solving the blind signal separation and deconvolution problems is provided. The susceptibilit

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23

Guddeti, Ram Mohana Reddy. "Perceptually motivated blind source separation of convolutive audio mixtures." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/12073.

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The first objective of this thesis is to apply psycho-acoustic principles to the spatial processing of speech signals in noisy and reverberant environment. The key assumption that will be adopted is that modern signal processing has failed to mimic the <i>cock-tail party effect</i> because there has been no attempt to adequately incorporate the psycho acoustical phenomenon of audio masking to aid source separation. A quasi linear mechanism for mimicking <i>simultaneous frequency</i> masking and<i> temporal masking</i> (post masking) techniques are developed. This frame work is used to construc

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24

Babaiezadeh, Malmiri Massoud. "On blind source separation in convolutive and nonlinear mixtures." Grenoble INPG, 2002. http://www.theses.fr/2002INPG0065.

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Dans cette thèse, la séparation aveugle de sources dans des mélanges convolutif Post Non-linéaire (CPNL) est étudiée. Pour séparer ce type de mélanges, nous avons d'abord développé des nouvelles méthodes pour séparer les mélanges convultifs et les mélanges Post Non-Linéaires (PNL). Ces méthodes sont toutes basées sur la minimisation de l'information mutuelle des sorties. Pour minimiser l'information mutuelle, nous calculons d'abord sa "différentielle", c'est-à-dire, sa variation en fonction d'une petite variation de son argument. Cette différentielle est alors utilisée pour concevoir des appro

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25

Riaz, Areeb. "Adaptive blind source separation based on intensity vector statistics." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/810208/.

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Human brain has the ability to focus on desired acoustic source when several sources are active. In the domain of digital electronics this problem is termed as the cock- tail party problem. Over the past few decades many algorithms have been proposed which attempt to solve this problem; they are generally termed as acoustic source separation algorithms. The proposed algorithms achieve separation of individual source components from observed acoustic mixtures. The source separation system may be capable of estimating the number of sources, their physical locations, the room impulse response and

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26

Zou, Liang. "Underdetermined joint blind source separation with application to physiological data." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/63013.

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Blind Source Separation (BSS) methods have been attracting increasing attention for their promising applications in signal processing. Despite recent progress on the research of BSS, there are still remaining challenges. Specifically, this dissertation focuses on developing novel Underdetermined Blind Source Separation (UBSS) methods that can deal with several specific challenges in real applications, including limited number of observations, self/cross dependence information and source inference in the underdetermined case. First, by taking advantage of the Noise Assisted Multivariate Empiri

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27

Kvernelv, Vegard Berg. "Optimization on Matrix Manifolds with Applications to Blind Source Separation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for fysikk, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-22688.

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Studere hvordan konsepter fra optimeringsteori generaliseres til mangfoldigheter, mer spesifikt matrisemangfoldigheter, og vurdere hvordan dette kan anvendes på "blind source separation"-problemer

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28

Wehr, Stefan [Verfasser]. "Robust Binaural Blind Source Separation in Hearing Aids / Stefan Wehr." München : Verlag Dr. Hut, 2013. http://d-nb.info/1031844627/34.

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29

Jafari, Maria Grazia. "Novel sequential algorithms for blind source separation of instantaneous mixtures." Thesis, King's College London (University of London), 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.397682.

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30

Remaggi, Luca. "Acoustic reflector localisation for blind source separation and spatial audio." Thesis, University of Surrey, 2017. http://epubs.surrey.ac.uk/842217/.

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From a physical point of view, sound is classically defined by wave functions. Like every other physical model based on waves, during its propagation, it interacts with the obstacles it encounters. These interactions result in reflections of the main signal that can be defined as either being supportive or interfering. In the signal processing research field, it is, therefore, important to identify these reflections, in order to either exploit or avoid them, respectively. The main contribution of this thesis focuses on the acoustic reflector localisation. Four novel methods are proposed: a met

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31

Sudhakara, Murthy Prasad. "Sparse models and convex optimisation for convolutive blind source separation." Rennes 1, 2011. https://tel.archives-ouvertes.fr/tel-00586610.

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Blind source separation from underdetermined mixtures is usually a two-step process: the estimation of the mixing filters, followed by that of the sources. An enabling assumption is that the sources are sparse and disjoint in the time-frequency domain. For convolutive mixtures, the solution is not straightforward due to the permutation and scaling ambiguities. The sparsity of the filters in the time-domain is also an enabling factor for blind filter estimation approaches that are based on cross-relation. However, such approaches are restricted to the single source setting. In this thesis, we j

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32

Roussos, Evangelos. "Bayesian methods for sparse data decomposition and blind source separation." Thesis, University of Oxford, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.589766.

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In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or 'sources' via a generally unknown mapping. Reconstructing sources from their mixtures is an extremely ill-posed problem in general. However, solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian method- ology, allowing us to incorporate "soft" constraints in a natural manner. This The

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Vikram, Anil Babu. "Tracking in wireless sensor network using blind source separation algorithms." Cleveland, Ohio : Cleveland State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=csu1259959597.

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Thesis (M.S.)--Cleveland State University, 2009.<br>Abstract. Title from PDF t.p. (viewed on Dec. 2, 2009). Includes bibliographical references (p. 65-72). Available online via the OhioLINK ETD Center and also available in print.

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Qi, Huan. "Video-based cardiac physiological measurements using joint blind source separation approaches." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54005.

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Non-contact measurements of human cardiopulmonary physiological parameters based on photoplethysmography (PPG) can lead to efficient and comfortable medical assessment. It was shown that human facial blood volume variation during cardiac cycle can be indirectly captured by regular Red-Green-Blue (RGB) cameras. However, few attempts have been made to incorporate data from different facial sub-regions to improve remote measurement performance. In this thesis, we propose a novel framework for non-contact video-based human heart rate (HR) measurement by exploring correlations among facial sub-regi

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35

Choi, Hyung Keun. "Blind source separation of the audio signals in a real world." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/14986.

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36

Abolghasemi, Vahid. "Advances in compressive sensing and its application in blind source separation." Thesis, University of Surrey, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543283.

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37

Kiani, Saeed. "Blind source separation in dynamic contrast enhanced magnetic resonance imaging renography." Thesis, University of Surrey, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616917.

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Dynamic contrast~enhanced magnetic resonance imaging (DCE-MRI) renography is a desirable kidney assessment methodology owing to the lack of ionizing radiation in MRI and its capability of producing high-resolution anatomical image data as well as physiological data. DCE-MRI renography emerged with the view to provide a minimally invasive framework to quickly and accurately assess kidney function, for example, to measure glomerular filtration rate (GFR). However, despite considerable developments, it is not yet considered a robust technique of renal assessment. This is due to a number of confou

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Stokes, Tobias W. "Improving the perceptual quality of single-channel blind audio source separation." Thesis, University of Surrey, 2015. http://epubs.surrey.ac.uk/807786/.

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Given a mixture of audio sources, a blind audio source separation (BASS) tool is required to extract audio relating to one specific source whilst attenuating that related to all others. This thesis answers the question “How can the perceptual quality of BASS be improved for broadcasting applications?” The most common source separation scenario, particularly in the field of broadcasting, is single channel, and this is particularly challenging as a limited set of cues are available. Broadcasting also requires that a source separator is automated, capable of handling non-stationary, reverberant m

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39

Lee, In Tae. "Machine learning algorithms for independent vector analysis and blind source separation." Diss., [La Jolla] : University of California, San Diego, 2009. http://wwwlib.umi.com/cr/ucsd/fullcit?p3373454.

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Thesis (Ph. D.)--University of California, San Diego, 2009.<br>Title from first page of PDF file (viewed October 22, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 59-63) and index.

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Domingo, Almenara Xavier. "Automated mass spectrometry-based metabolomics data processing by blind source separation methods." Doctoral thesis, Universitat Rovira i Virgili, 2016. http://hdl.handle.net/10803/397799.

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Una de les principals limitacions de la metabolòmica és la transformació de dades crues en informació biològica. A més, la metabolòmica basada en espectrometria de masses genera grans quantitats de dades complexes caracteritzades per la co-elució de compostos i artefactes experimentals. L'objectiu d'aquesta tesi és desenvolupar estratègies automatitzades basades en deconvolució cega del senyal per millorar les capacitats dels mètodes existents que tracten les limitacions de les diferents passes del processament de dades en metabolòmica. L'objectiu d'aquesta tesi és també desenvolupar eine

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Kokkinakis, Konstantinos. "Multichannel blind deconvolution methods for source separation in convolutive mixtures of speech." Thesis, University of Liverpool, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426119.

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Wedekind, Daniel, Alexander Trumpp, Frederik Gaetjen, et al. "Assessment of blind source separation techniques for video-based cardiac pulse extraction." SPIE, 2017. https://tud.qucosa.de/id/qucosa%3A35267.

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Blind source separation (BSS) aims at separating useful signal content from distortions. In the contactless acquisition of vital signs by means of the camera-based photoplethysmogram (cbPPG), BSS has evolved the most widely used approach to extract the cardiac pulse. Despite its frequent application, there is no consensus about the optimal usage of BSS and its general benefit. This contribution investigates the performance of BSS to enhance the cardiac pulse from cbPPGs in dependency to varying input data characteristics. The BSS input conditions are controlled by an automated spatial preselec

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Chao, Jih-Cheng. "On the design of robust criteria and algorithms for blind source separation." Ann Arbor, Mich. : ProQuest, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3284333.

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Thesis (Ph.D. in Electrical Engineering)--S.M.U., 2007.<br>Title from PDF title page (viewed Nov. 19, 2009). Source: Dissertation Abstracts International, Volume: 68-11, Section: B, page: 7530. Adviser: Scott C. Douglas. Includes bibliographical references.

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Gascon-Pelegri, Vicente Zarzoso. "Closed-form higher-order estimators for blind separation of independent source signals in instantaneous linear mixtures." Thesis, University of Liverpool, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343754.

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El, halabi Ramzi. "Blind source separation of single-sensor recordings : Application to ground reaction force signals." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSES031/document.

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Les signaux multicanaux sont des signaux captés à travers plusieurs canaux ou capteurs, portant chacun un mélange de sources, une partie desquelles est connue alors que le reste des sources reste inconnu. Les méthodes à l’aide desquelles l’isolement ou la séparation des sources est accomplie sont connues par les méthodes de séparation de sources en général, et si le degré d’inconnu est large, par la séparation aveugle des sources (SAS). Cependant, la SAS appliquée aux signaux multicanaux est en fait plus facile de point de vue mathématique que l’application de la SAS sur des signaux monocanaux

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Picquenot, Adrien. "Introduction and application of a new blind source separation method for extended sources in X-ray astronomy." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASP028.

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Certaines sources étendues, telles que les vestiges de supernovae, présentent en rayons X une remarquable diversité de morphologie que les téléscopes de spectro-imagerie actuels parviennent à détecter avec un exceptionnel niveau de précision. Cependant, les outils d’analyse actuellement utilisés dans l’étude des phénomènes astrophysiques à haute énergie peinent à exploiter pleinement le potentiel de ces données : les méthodes d’analyse standard se concentrent sur l’information spectrale sans exploiter la multiplicité des morphologies ni les corrélations existant entre les dimensions spatiales

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Harris, Jack D. "Online source separation in reverberant environments exploiting known speaker locations." Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/19627.

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This thesis concerns blind source separation techniques using second order statistics and higher order statistics for reverberant environments. A focus of the thesis is algorithmic simplicity with a view to the algorithms being implemented in their online forms. The main challenge of blind source separation applications is to handle reverberant acoustic environments; a further complication is changes in the acoustic environment such as when human speakers physically move. A novel time-domain method which utilises a pair of finite impulse response filters is proposed. The method of principle an

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Cheong, Took Clive. "Blind source separation via independent and sparse component analysis with application to temporomandibular disorder." Thesis, Cardiff University, 2007. http://orca.cf.ac.uk/54590/.

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Blind source separation (BSS) addresses the problem of separating multi channel signals observed by generally spatially separated sensors into their constituent underlying sources. The passage of these sources through an unknown mixing medium results in these observed multichannel signals. This study focuses on BSS, with special emphasis on its application to the temporomandibular joint disorder (TMD). TMD refers to all medical problems related to the temporomandibular joint (TMJ), which holds the lower jaw (mandible) and the temporal bone (skull). The overall objective of the work is to extra

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Hattay, Jamel. "Wavelet-based lifting structures and blind source separation : applications to digital in-line holography." Rouen, 2016. http://www.theses.fr/2016ROUES016.

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Ce projet de thèse expose des méthodes de traitement, dans le domaine des ondelettes, pour résoudre certains problèmes liés à la mise en oeuvre de l’holographie numérique dans l’axe. Ce developpement utilise des outils de la théorie de l’information et des divers moyens de traitement du signal tels que la séparation aveugle de sources (SAS). Cette technique est exploitée, ici, pour améliorer l’efficacité de l’holographie numérique, tels que la suppression de l’image jumelle, l’estimation de l’indice de réfraction, le codage et la transmission temps réel des hologrammes. Tout d’abord, nous donn

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Wang, Niya. "Unsupervised Signal Deconvolution for Multiscale Characterization of Tissue Heterogeneity." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/73772.

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Characterizing complex tissues requires precise identification of distinctive cell types, cell-specific signatures, and subpopulation proportions. Tissue heterogeneity, arising from multiple cell types, is a major confounding factor in studying individual subpopulations and repopulation dynamics. Tissue heterogeneity cannot be resolved directly by most global molecular and genomic profiling methods. While signal deconvolution has widespread applications in many real-world problems, there are significant limitations associated with existing methods, mainly unrealistic assumptions and heuristics

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