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IEEE Signal Processing Magazine

Issue 6 • Date Nov. 2010

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Displaying Results 1 - 25 of 25
  • [Front cover]

    Publication Year: 2010, Page(s): C1
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  • [Table of Contents]

    Publication Year: 2010, Page(s): 1
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  • Impact of Signal Processing and of Our Work [From the Editor]

    Publication Year: 2010, Page(s):2 - 12
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  • Staff listing

    Publication Year: 2010, Page(s): 2
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  • IEEE-SPS: Your Professional Home [President's Message]

    Publication Year: 2010, Page(s): 4
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  • Trends In Video Surveillance Give DSP an Apps Boost [Special Reports]

    Publication Year: 2010, Page(s):6 - 12
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (729 KB) | HTML iconHTML

    They're everywhere. Literally millions of video surveillance cameras tracking our every move just about everywhere in the world. And you can't even see most of them. View full abstract»

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  • Top Downloads in IEEE Xplore [Readers Choice]

    Publication Year: 2010, Page(s):13 - 16
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  • Major Advances and Emerging Developments of Graphical Models [From the Guest Editors]

    Publication Year: 2010, Page(s):17 - 138
    Cited by:  Papers (4)
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  • Graphical Models for Time-Series

    Publication Year: 2010, Page(s):18 - 28
    Cited by:  Papers (16)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1389 KB) | HTML iconHTML

    Time-series analysis is central to many problems in signal processing, including acoustics, image processing, vision, tracking, information retrieval, and finance, to name a few. Because of the wide base of application areas, having a common description of the models is useful in transferring ideas between the various communities. Graphical models provide a compact way to represent such models and... View full abstract»

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  • Dynamic Graphical Models

    Publication Year: 2010, Page(s):29 - 42
    Cited by:  Papers (5)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1092 KB) | HTML iconHTML

    A graphical model consists of I a graph G = (V,E) and a V set of properties that determine a family of V probability distributions. There are many different types of graphs and properties, each determining a family. It is common to be able to develop algorithms that work for all members of the family by considering only a graph and its properties. Thus, solving difficult problems (such as deriving... View full abstract»

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  • Bayesian Nonparametric Methods for Learning Markov Switching Processes

    Publication Year: 2010, Page(s):43 - 54
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1145 KB) | HTML iconHTML

    In this article, we explored a Bayesian nonparametric approach to learning Markov switching processes. This framework requires one to make fewer assumptions about the underlying dynamics, and thereby allows the data to drive the complexity of the inferred model. We began by examining a Bayesian nonparametric HMM, the sticky HDPHMM, that uses a hierarchical DP prior to regularize an unbounded mode ... View full abstract»

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  • Probabilistic Topic Models

    Publication Year: 2010, Page(s):55 - 65
    Cited by:  Papers (25)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3134 KB) | HTML iconHTML

    In this article, we review probabilistic topic models: graphical models that can be used to summarize a large collection of documents with a smaller number of distributions over words. Those distributions are called "topics" because, when fit to data, they capture the salient themes that run through the collection. We describe both finite-dimensional parametric topic models and their Bayesian nonp... View full abstract»

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  • Single-Channel Multitalker Speech Recognition

    Publication Year: 2010, Page(s):66 - 80
    Cited by:  Papers (26)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1932 KB) | HTML iconHTML

    We have described some of the problems with modeling mixed acoustic signals in the log spectral domain using graphical models, as well as some current approaches to handling these problems for multitalker speech separation and recognition. We have also reviewed methods for inference on FHMMs (factorial hidden Markov model) and methods for handling the nonlinear interaction function in the log spec... View full abstract»

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  • Variational Bayesian Inference Techniques

    Publication Year: 2010, Page(s):81 - 91
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2454 KB) | HTML iconHTML

    Milestones in sparse signal reconstruction and compressive sensing can be understood in a probabilistic Bayesian context, fusing underdetermined measurements with knowledge about low-level signal properties in the posterior distribution, which is maximized for point estimation. We review recent progress to advance beyond this setting. If the posterior is used as a distribution to be integrated ove... View full abstract»

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  • Sparse Signal Recovery and Acquisition with Graphical Models

    Publication Year: 2010, Page(s):92 - 103
    Cited by:  Papers (17)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2161 KB) | HTML iconHTML

    A great deal of theoretic and algorithmic research has revolved around sparsity view of signals over the last decade to characterize new, sub-Nyquist sampling limits as well as tractable algorithms for signal recovery from dimensionality reduced measurements. Despite the promising advances made, real-life applications require more realistic signal models that can capture the underlying, applicatio... View full abstract»

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  • Joint Source and Channel Coding

    Publication Year: 2010, Page(s):104 - 113
    Cited by:  Papers (21)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (784 KB) | HTML iconHTML

    The objectives of this article are two-fold: First, to present the problem of joint source and channel (JSC) coding from a graphical model perspective and second, to propose a structure that uses a new graphical model for jointly encoding and decoding a redundant source. In the first part of the article, relevant contributions to JSC coding, ranging from the Slepian-Wolf problem to joint decoding ... View full abstract»

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  • Practical Issues in Implementing a Single-Pole Low-Pass IIR Filter [Applications Corner]

    Publication Year: 2010, Page(s):114 - 117
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (113 KB) | HTML iconHTML

    Infinite-impulse response (IIR) filters are one of the primary types of digital filters in digital signal processing (DSP) systems. Among many different IIR filters, a single-pole low-pass may be the most widely used filter in various applications. View full abstract»

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  • A Geometric Perspective of Large-Margin Training of Gaussian Models [Lecture Notes]

    Publication Year: 2010, Page(s):118 - 123
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (318 KB) | HTML iconHTML

    Large-margin techniques have been studied intensively by the machine learning community to balance the empirical error rate on the training set and the generalization ability on the test set. However, they have been mostly developed together with generic discriminative models such as support vector machines (SVMs) and are often difficult to apply in parameter estimation problems for generative mod... View full abstract»

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  • Accurate, Guaranteed Stable, Sliding Discrete Fourier Transform [DSP Tips & Tricks]

    Publication Year: 2010, Page(s):124 - 127
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (267 KB) | HTML iconHTML

    This article presented a novel method of computing the SDFT that we call the modulated SDFT (mSDFT). The sliding discrete Fourier transform (SDFT) is a recursive algorithm that computes a DFT on a sample-by-sample basis. The accumulated errors and potential instabilities inherent in traditional SDFT algorithms are drastically reduced in the mSDFT. We removed the twiddle factor from the feedback in... View full abstract»

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  • Advances in Behavioral Science Using Automated Facial Image Analysis and Synthesis [Social Sciences]

    Publication Year: 2010, Page(s):128 - 133
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1874 KB) | HTML iconHTML

    The face conveys information about a person's age, sex, background, and identity; what they are feeling, thinking, or likely to do next. Facial expression regulates face-to-face interactions, indicates reciprocity and interpersonal attraction or repulsion, and enables intersubjectivity between members of different cultures. Facial expression indexes neurological and psychiatric functioning and rev... View full abstract»

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  • 3GPP Mobile Multimedia Streaming Standards [Standards in a Nutshell]

    Publication Year: 2010, Page(s):134 - 138
    Cited by:  Papers (7)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (209 KB) | HTML iconHTML

    Data rates offered by mobile networks are increasing, as are the capabilities of mobile devices. With this, mobile multimedia services are getting wider distribution. Traditional linear mobile TV services, where the viewer has to watch a scheduled TV program at the offered time, were initially dominating but other streaming services like Video on Demand, User-Generated Content (USG) services, or I... View full abstract»

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  • TechWare: Speaker and Spoken Language Recognition Resources [Best of the Web]

    Publication Year: 2010, Page(s):139 - 142
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (268 KB) | HTML iconHTML

    In this issue, "Best of the Web" focuses on speaker and spoken language recognition technology. Speaker recognition is a computing task to establish or to verify the speaker's identity using the speaker's voice. Similarly, spoken language recognition is a task to identify or to confirm the language, dialect or accent that is spoken given a speech sample. The latter is also referred to as language ... View full abstract»

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  • [Dates Ahead]

    Publication Year: 2010, Page(s): 143
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  • [2010 Annual Index]

    Publication Year: 2010, Page(s):144 - 156
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  • Lightwave Neuromorphic Signal Processing [In The Spotlight]

    Publication Year: 2010, Page(s):160 - 158
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (525 KB) | HTML iconHTML

    This article discusses a technique that promises to deliver improved optical computing. Specifically, neuromorphic engineering that can inspire novel optical computing devices. Neuromorphic engineering aims to develop practical computing and signal processing devices based on an understanding of the biophysics of neuronal computation. View full abstract»

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Aims & Scope

IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest. Its coverage ranges from fundamental principles to practical implementation, reflecting the multidimensional facets of interests and concerns of the community. Its mission is to bring up-to-date, emerging and active technical developments, issues, and events to the research, educational, and professional communities. It is also the main Society communication platform addressing important issues concerning all members.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Min Wu
University of Maryland, College Park
United States 

http://www/ece.umd.edu/~minwu/