Showing papers by "University of Illinois at Urbana–Champaign published in 2002"

Detecting faces in images: a survey

Abstract: Images containing faces are essential to intelligent vision-based human-computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face, regardless of its 3D position, orientation and lighting conditions. Such a problem is challenging because faces are non-rigid and have a high degree of variability in size, shape, color and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research.

Principles and practice in reporting structural equation analyses.

Abstract: Principles for reporting analyses using structural equation modeling are reviewed, with the goal of supplying readers with complete and accurate information. It is recommended that every report give a detailed justification of the model used, along with plausible alternatives and an account of identifiability. Nonnormality and missing data problems should also be addressed. A complete set of parameters and their standard errors is desirable, and it will often be convenient to supply the correlation matrix and discrepancies, as well as goodness-of-fit indices, so that readers can exercise independent critical judgment. A survey of fairly representative studies compares recent practice with the principles of reporting recommended here. Structural equation modeling (SEM), also known as path analysis with latent variables, is now a regularly used method for representing dependency (arguably “causal”) relations in multivariate data in the behavioral and social sciences. Following the seminal

The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity.

Abstract: The authors present a unified account of 2 neural systems concerned with the development and expression of adaptive behaviors: a mesencephalic dopamine system for reinforcement learning and a “generic” error-processing system associated with the anterior cingulate cortex The existence of the error-processing system has been inferred from the error-related negativity (ERN), a component of the event-related brain potential elicited when human participants commit errors in reaction-time tasks The authors propose that the ERN is generated when a negative reinforcement learning signal is conveyed to the anterior cingulate cortex via the mesencephalic dopamine system and that this signal is used by the anterior cingulate cortex to modify performance on the task at hand They provide support for this proposal using both computational modeling and psychophysiological experimentation

Opportunistic beamforming using dumb antennas

Abstract: Multiuser diversity is a form of diversity inherent in a wireless network, provided by independent time-varying channels across the different users. The diversity benefit is exploited by tracking the channel fluctuations of the users and scheduling transmissions to users when their instantaneous channel quality is near the peak. The diversity gain increases with the dynamic range of the fluctuations and is thus limited in environments with little scattering and/or slow fading. In such environments, we propose the use of multiple transmit antennas to induce large and fast channel fluctuations so that multiuser diversity can still be exploited. The scheme can be interpreted as opportunistic beamforming and we show that true beamforming gains can be achieved when there are sufficient users, even though very limited channel feedback is needed. Furthermore, in a cellular system, the scheme plays an additional role of opportunistic nulling of the interference created on users of adjacent cells. We discuss the design implications of implementing. this scheme in a complete wireless system.

Computer Vision: A Modern Approach

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Coverage control for mobile sensing networks

Abstract: This paper describes decentralized control laws for the coordination of multiple vehicles performing spatially distributed tasks. The control laws are based on a gradient descent scheme applied to a class of decentralized utility functions that encode optimal coverage and sensing policies. These utility functions are studied in geographical optimization problems and they arise naturally in vector quantization and in sensor allocation tasks. The approach exploits the computational geometry of spatial structures such as Voronoi diagrams.

gSpan: graph-based substructure pattern mining

Abstract: We investigate new approaches for frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan (graph-based substructure pattern mining), which discovers frequent substructures without candidate generation. gSpan builds a new lexicographic order among graphs, and maps each graph to a unique minimum DFS code as its canonical label. Based on this lexicographic order gSpan adopts the depth-first search strategy to mine frequent connected subgraphs efficiently. Our performance study shows that gSpan substantially outperforms previous algorithms, sometimes by an order of magnitude.

Coverage control for mobile sensing networks

Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Very Happy People

Abstract: A sample of 222 undergraduates was screened for high happiness using multiple confirming assessment filters. We compared the upper 10% of consistently very happy people with average and very unhappy people. The very happy people were highly social, and had stronger romantic and other social relationships than less happy groups. They were more extraverted, more agreeable, and less neu- rotic, and scored lower on several psychopathology scales of the Min- nesota Multiphasic Personality Inventory. Compared with the less happy groups, the happiest respondents did not exercise significantly more, participate in religious activities significantly more, or experi- ence more objectively defined good events. No variable was sufficient for happiness, but good social relations were necessary. Members of the happiest group experienced positive, but not ecstatic, feelings most of the time, and they reported occasional negative moods. This sug- gests that very happy people do have a functioning emotion system that can react appropriately to life events. Investigations of very unhappy individuals, such as people with anxiety and mood disorders, abound in the psychological literature (Myers, 2000). In contrast, investigations of happy people are rare, and investigations of very happy people do not exist. This imbalance probably stems from clinical psychology's historic emphasis on pa- thology, coupled with the belief that understanding abnormal pro- cesses can illuminate normal processes. We have the complementary belief: that understanding "supranormal" individuals can illuminate normal processes, and that knowing how very happy people function might provide information on how to buffer very unhappy people against psychopathology (Seligman & Csikszentmihalyi, 2000). We report here the first study of the behavioral and personality correlates of high happiness. In this study, we examined some factors that seem likely to influence high happiness: social relationships, personality and psychopathology, and variables (e.g., religiosity and exercise) that have been related to subjective well-being in correlational studies. In addition to examining how the happiest respondents compared with the average and with very unhappy respondents on these variables, we examined the patterns of necessity and sufficiency. For a variable to be sufficient for happiness, all persons with that variable should be happy (i.e., if X , always happy)- and therefore virtually no unhappy people should possess the variable. For a variable to be necessary for happiness, virtually every happy per- son should possess that variable (i.e., if happy, then X ). Thus, in these analyses, we examined whether there is a "key" to happiness—a vari- able that is both necessary and sufficient for happiness. A third purpose of the study was to examine the moods and emo- tions of the happiest individuals. Did they experience mostly euphoric feelings or only moderate positive emotions on most occasions? Did they experience occasional unpleasant emotions? If the happiest peo- ple never experienced negative emotions and were locked into eu- phoric feelings, the state might be dysfunctional because these individuals would not react to the events happening to them and would not receive calibrated feedback from their emotions.

Topological Persistence and Simplification

Abstract: We formalize a notion of topological simplification within the framework of a filtration, which is the history of a growing complex. We classify a topological change that happens during growth as either a feature or noise depending on its lifetime or persistence within the filtration. We give fast algorithms for computing persistence and experimental evidence for their speed and utility.

Views of nature of science questionnaire: Toward valid and meaningful assessment of learners' conceptions of nature of science

Abstract: Helping students develop informed views of nature of science (NOS) has been and continues to be a central goal for kindergarten through Grade 12 (K–12) science education. Since the early 1960s, major efforts have been undertaken to enhance K–12 students and science teachers' NOS views. However, the crucial component of assessing learners' NOS views remains an issue in research on NOS. This article aims to (a) trace the development of a new open-ended instrument, the Views of Nature of Science Questionnaire (VNOS), which in conjunction with individual interviews aims to provide meaningful assessments of learners' NOS views; (b) outline the NOS framework that underlies the development of the VNOS; (c) present evidence regarding the validity of the VNOS; (d) elucidate the use of the VNOS and associated interviews, and the range of NOS aspects that it aims to assess; and (e) discuss the usefulness of rich descriptive NOS profiles that the VNOS provides in research related to teaching and learning about NOS. The VNOS comes in response to some calls within the science education community to go back to developing standardized forced-choice paper and pencil NOS assessment instruments designed for mass administrations to large samples. We believe that these calls ignore much of what was learned from research on teaching and learning about NOS over the past 30 years. The present state of this line of research necessitates a focus on individual classroom interventions aimed at enhancing learners' NOS views, rather than on mass assessments aimed at describing or evaluating students' beliefs. © 2002 Wiley Periodicals, Inc. J Res Sci Teach 39: 497–521, 2002

Probabilistic Basis for 2000 SAC Federal Emergency Management Agency Steel Moment Frame Guidelines

Abstract: This paper presents a formal probabilistic framework for seismic design and assessment of structures and its application to steel moment-resisting frame buildings. This is the probabilistic basis for the 2000 SAC Federal Emergency Management Agency ~FEMA! steel moment frame guidelines. The framework is based on realizing a performance objective expressed as the probability of exceeding a specified performance level. Performance levels are quantified as expressions relating generic structural variables ''demand'' and ''capacity'' that are described by nonlinear, dynamic displacements of the structure. Common probabilistic analysis tools are used to convolve both the randomness and uncertainty characteristics of ground motion intensity, structural ''demand,'' and structural system ''capacity'' in order to derive an expression for the probability of achieving the specified performance level. Stemming from this probabilistic framework, a safety-checking format of the conventional ''load and resistance factor'' kind is developed with load and resistance terms being replaced by the more generic terms ''demand'' and ''capacity,'' respectively. This framework also allows for a format based on quantitative confidence statements regarding the likelihood of the performance objective being met. This format has been adopted in the SAC/FEMA guidelines.

Advanced Technology Paths to Global Climate Stability: Energy for a Greenhouse Planet

Abstract: Stabilizing the carbon dioxide-induced component of climate change is an energy problem. Establishment of a course toward such stabilization will require the development within the coming decades of primary energy sources that do not emit carbon dioxide to the atmosphere, in addition to efforts to reduce end-use energy demand. Mid-century primary power requirements that are free of carbon dioxide emissions could be several times what we now derive from fossil fuels (approximately 10(13) watts), even with improvements in energy efficiency. Here we survey possible future energy sources, evaluated for their capability to supply massive amounts of carbon emission-free energy and for their potential for large-scale commercialization. Possible candidates for primary energy sources include terrestrial solar and wind energy, solar power satellites, biomass, nuclear fission, nuclear fusion, fission-fusion hybrids, and fossil fuels from which carbon has been sequestered. Non-primary power technologies that could contribute to climate stabilization include efficiency improvements, hydrogen production, storage and transport, superconducting global electric grids, and geoengineering. All of these approaches currently have severe deficiencies that limit their ability to stabilize global climate. We conclude that a broad range of intensive research and development is urgently needed to produce technological options that can allow both climate stabilization and economic development.

Learning question classifiers

Abstract: In order to respond correctly to a free form factual question given a large collection of texts, one needs to understand the question to a level that allows determining some of the constraints the question imposes on a possible answer. These constraints may include a semantic classification of the sought after answer and may even suggest using different strategies when looking for and verifying a candidate answer.This paper presents a machine learning approach to question classification. We learn a hierarchical classifier that is guided by a layered semantic hierarchy of answer types, and eventually classifies questions into fine-grained classes. We show accurate results on a large collection of free-form questions used in TREC 10.

Economic Status and Health in Childhood: The Origins of the Gradient

Abstract: The well-known positive association between health and income in adulthood has antecedents in childhood. Not only is children’s health positively related to household income, but the relationship between household income and children's health becomes more pronounced as children age. Part of the relationship can be explained by the arrival and impact of chronic conditions. Children from lower income households with chronic conditions have worse health than do those from higher-income households. The adverse health effects of lower income accumulate over children’s lives. Part of the intergenerational transmission of socioeconomic status may work through the impact of parents' income on children’s health.

Will Money Increase Subjective Well-Being?

Abstract: Four replicable findings have emerged regarding the relation between income and subjective well-being (SWB): 1. There are large correlations between the wealth of nations and the mean reports of SWB in them, 2. There are mostly small correlations between income and SWB within nations, although these correlations appear to be larger in poor nations, and the risk of unhappiness is much higher for poor people, 3. Economic growth in the last decades in most economically developed societies has been accompanied by little rise in SWB, and increases in individual income lead to variable outcomes, and 4. People who prize material goals more than other values tend to be substantially less happy, unless they are rich. Thus, more money may enhance SWB when it means avoiding poverty and living in a developed nation, but income appears to increase SWB little over the long-term when more of it is gained by well-off individuals whose material desires rise with their incomes. Several major theories are compatible with most existing findings: A. The idea that income enhances SWB only insofar as it helps people meet their basic needs, and B. The idea that the relation between income and SWB depends on the amount of material desires that people's income allows them to fulfill. We argue that the first explanation is a special case of the second one. A third explanation is relatively unresearched, the idea that societal norms for production and consumption are essential to understanding the SWB-income interface. In addition, it appears high SWB might increase people's chances for high income. We review the open issues relating income to SWB, and describe the research methods needed to provide improved data that will better illuminate the psychological processes relating money to SWB.

Turbo equalization: principles and new results

Abstract: We study the turbo equalization approach to coded data transmission over channels with intersymbol interference. In the original system invented by Douillard et al. (1995), the data are protected by a convolutional code and the receiver consists of two trellis-based detectors, one for the channel (the equalizer) and one for the code (the decoder). It has been shown that iterating equalization and decoding tasks can yield tremendous improvements in bit error rate. We introduce new approaches to combining equalization based on linear filtering, with decoding.. Through simulation and analytical results, we show that the performance of the new approaches is similar to the trellis-based receiver, while providing large savings in computational complexity. Moreover, this paper provides an overview of the design alternatives for turbo equalization with given system parameters, such as the channel response or the signal-to-noise ratio.

A design theory for systems that support emergent knowledge processes

Abstract: This paper addresses the design problem of providing IT support for emerging knowledge processes (EKPs). EKPs are organizational activity patterns that exhibit three characteristics in combination: an emergent process of deliberations with no best structure or sequence; requirements for knowledge that are complex (both general and situational), distributed across people, and evolving dynamically; and an actor set that is unpredictable in terms of job roles or prior knowledge. Examples of EKPs include basic research, new product development, strategic business planning, and organization design. EKPs differ qualitatively from semi-structured decision making processes; therefore, they have unique requirements that are not all thoroughly supported by familiar classes of systems, such as executive information systems, expert systems, electronic communication systems, organizational memory systems, or repositories. Further, the development literature on familiar classes of systems does not provide adequate guidance on how to build systems that support EKPs. Consequently, EKPs require a new IS design theory, as explicated by Walls et al. (1992). We created such a theory while designing and deploying a system for the EKP of organization design. The system was demonstrated through subsequent empirical analysis to be successful in supporting the process. Abstracting from the experience of building this system, we developed an IS design theory for EKP support systems. This new IS design theory is an important theoretical contribution, because it both provides guidance to developers and sets an agenda for academic research. EKP design theory makes the development process more tractable for developers by restricting the range of effective features (or rules for selecting features) and the range of effective development practices to a more manageable set. EKP design theory also sets an agenda for academic research by articulating theory-based principles that are subject to empirical, as well as practical, validation.

A middleware infrastructure for active spaces

Abstract: The paper discusses the Gaia metaoperating system which extends the reach of traditional operating systems to manage ubiquitous computing habitats and living spaces as integrated programmable environments. Gaia exports services to query, access, and use existing resources and context, and provides a framework to develop user-centric, resource-aware, multidevice, context-sensitive, and mobile applications.

Persuasion: Theory and Research

Abstract: Preface Chapter 1: Persuasion, Attitudes, and Actions The Concept of Persuasion The Concept of Attitude Attitude Measurement Techniques Attitudes and Behaviors Assessing Persuasive Effects Conclusion Notes Chapter 2: Social Judgment Theory Judgments of Alternative Positions on an Issue Reactions to Communications Critical Assessment Conclusion Notes Chapter 3: Functional Approaches to Attitude A Classic Functional Analysis Subsequent Developments Commentary Conclusion Notes Chapter 4: Belief-Based Models of Attitude Summative Model of Attitude Research Evidence and Commentary Conclusion Notes Chapter 5: Cognitive Dissonance Theory General Theoretical Sketch Some Research Applications Revisions of, And Alternatives to, Dissonance Theory Conclusion Notes Chapter 6: Reasoned Action Theory The Reasoned Action Theory Model Influencing Intentions Intentions and Behaviors Adapting Persuasive Messages to Recipients Based on Reasoned Action Theory Commentary Conclusion Notes Chapter 7: Stage Models The Transtheoretical Model The Distinctive Claims of Stage Models Other Stage Models Conclusion Notes Chapter 8: Elaboration Likelihood Model Variations in the Degree of Elaboration: Central versus Peripheral Routes to Persuasion Factors Affecting the Degree of Elaboration Influences on Persuasive Effects under Conditions of High Elaboration: Central Routes to Persuasion Influences on Persuasive Effects under Conditions of Low Elaboration: Peripheral Routes to Persuasion Multiple Roles for Persuasion Variables Adapting Persuasive Messages to Recipients Based on the ELM Commentary Conclusion Notes Chapter 9: The Study of Persuasive Effects Experimental Design and Causal Inference Two General Challenges in Studying Persuasive Effects Conclusion Notes Chapter 10: Communicator Factors Communicator Credibility Liking Other Communicator Factors Conclusion Notes Chapter 11: Message Factors Message Structure and Format Message Content Sequential Request Strategies Conclusion Notes Chapter 12: Receiver Factors Individual Differences Transient Receiver States Influencing Susceptibility to Persuasion Conclusion Notes References Author Index Subject Index About the Author

The Internet in everyday life

Abstract: List of Figures. List of Tables. Foreword: The Virtual Community in the Real World. (Howard Rheingold). Series Editora s Preface: The Internet and the Network Society . (Manuel Castells). Introduction: The Internet in Everyday Life. (Caroline Haythornthwaite and Barry Wellman). Part I: Moving The Internet Out Of Cyberspace. The internet in Everyday Life: An Introduction. (Caroline Haythornthwaite and Barry Wellman). Part II: The Place Of The Internet In Everyday Life. 1. Days and Nights on the Internet. (Philip Howard, Lee Rainie, and Steve Jones). 2 The Global Villagers: Comparing Internet Users and Uses Around the World. (Wenhong Chen, Jeffrey Boase and Barry Wellman). 3 Syntopia: Access, Civic Involvement and Social Interaction on the Net. (James Katz and Ronald Rice). 4 Digital Living: The Impact (or Otherwise) of the Internet in Everyday British Life. (Ben Anderson and Karina Tracey). 5 The Changing Digital Divide in Germany. (Gert Wagner, Rainer Pischner and John Haisken--DeNew). 6 Doing Social Science Research Online . (Alan Neustadtl, John Robinson and Meyer Kestnbaum). Part III: Finding Time For The Internet. 7 Internet Use, Interpersonal Relations and Sociability: A Time Diary Study. (Norman Nie, D. Sunshine Hillygus and Lutz Erbring). 8 The Internet and Other Uses of Time. (John Robinson, Meyer Kestnbaum, Alan Neustadtl and Anthony Alvarez). 9 Everyday Communication Patterns of Heavy and Light Email Users. (Janell Copher, Alaina Kanfer and Mary Bea Walker). Part IV: The Internet In The Community. 10 Capitalizing on the Net: Social Contact, Civic Engagement and Sense of Community. (Anabel Quan--Haase and Barry Wellman). 11 The Impact of Computer Networks on Social Capital and Community Involvement in Blacksburg. (Andrea Kavanaugh and Scott Patterson). 12 The Not So Global Village of Netville. (Keith Hampton and Barry Wellman). 13 Gender and Personal Relationships in HomeNet. (Bonka Boneva and Robert Kraut). 14 Belonging in Geographic, Ethnic and Internet Spaces. (Sorin Matei and Sandra Ball--Rokeach). Part V: The Internet At School, Work And Home. 15 Bringing the Internet Home: Adult distance learners and their Internet, Home and Work worlds. (Caroline Haythornthwaite and Michelle Kazmer). 16 Where Home is the Office: The New Form of Flexible Work. (Janet Salaff). 17 Kerala Connections: Will the Internet Affect Science in Developing Areas?. (Teresa Davidson, R. Sooryamoorthy and Wesley Shrum). 18 Social Support for Japanese Mothers Online and Offline . (Kakuko Miyata). 19 Shopping Behavior Online. (Robert Lunn and Michael Suman). Index

Cultural Influences on Personality

Abstract: Ecologies shape cultures; cultures influence the development of personalities. There are both universal and culture-specific aspects of variation in personality. Some culture-specific aspects correspond to cultural syndromes such as complexity, tightness, individualism, and collectivism. A large body of literature suggests that the Big Five personality factors emerge in various cultures. However, caution is required in arguing for such universality, because most studies have not included emic (culture-specific) traits and have not studied samples that are extremely different in culture from Western samples.

Conceptualizing and Measuring Democracy. Evaluating Alternative Indices

Abstract: A comprehensive and integrated framework for the analysis of data is offered and used to assess data sets on democracy. The framework first distinguishes among three challenges that are sequentially addressed: conceptualization, measurement, and aggregation. In turn, it specifies distinct tasks associated with these challenges and the standards of assessment that pertain to each task. This framework is applied to the data sets on democracy most frequently used in current statistical research, generating a systematic evaluation of these data sets. The authors’ conclusion is that constructors of democracy indices tend to be quite self-conscious about methodological issues but that even the best indices suffer from important weaknesses. More constructively, the article’s assessment of existing data sets on democracy identifies distinct areas in which attempts to improve the quality of data on democracy might fruitfully be focused.

Conceptualizing and Measuring Democracy Evaluating Alternative Indices

Abstract: A comprehensive and integrated framework for the analysis of data is offered and used to assess data sets on democracy. The framework first distinguishes among three challenges that are sequentially addressed: conceptualization, measurement, and aggregation. In turn, it specifies distinct tasks associated with these challenges and the standards of assessment that pertain to each task. This framework is applied to the data sets on democracy most frequently used in current statistical research, generating a systematic evaluation of these data sets. The authors’ conclusion is that constructors of democracy indices tend to be quite self-conscious about methodological issues but that even the best indices suffer from important weaknesses. More constructively, the article’s assessment of existing data sets on democracy identifies distinct areas in which attempts to improve the quality of data on democracy might fruitfully be focused.

A meta-analysis of team-efficacy, potency, and performance: interdependence and level of analysis as moderators of observed relationships.

Abstract: Meta-analytic techniques were used to examine level of analysis and interdependence as moderators of observed relationships between task-specific team-efficacy, generalized potency, and performance. Sixty-seven empirical studies yielding 256 effect sizes were identified and meta-analyzed. Results demonstrated that relationships are moderated by level of analysis. Effect sizes were stronger at the team level (p = .39) than at the individual level (p = .20). At the team level, both team-efficacy and potency had positive relationships with performance (ps = .41 and .37, respectively). Interdependence significantly moderated the relationship between team-efficacy and performance, but not between potency and performance. The relationship between team-efficacy and performance was stronger when interdependence was high (p = .45) than when it was low (p = .34).

On the capacity of OFDM-based spatial multiplexing systems

Abstract: This paper deals with the capacity behavior of wireless orthogonal frequency-division multiplexing (OFDM)-based spatial multiplexing systems in broad-band fading environments for the case where the channel is unknown at the transmitter and perfectly known at the receiver Introducing a physically motivated multiple-input multiple-output (MIMO) broad-band fading channel model, we study the influence of physical parameters such as the amount of delay spread, cluster angle spread, and total angle spread, and system parameters such as the number of antennas and antenna spacing on ergodic capacity and outage capacity We find that, in the MIMO case, unlike the single-input single-output (SISO) case, delay spread channels may provide advantages over flat fading channels not only in terms of outage capacity but also in terms of ergodic capacity Therefore, MIMO delay spread channels will in general provide both higher diversity gain and higher multiplexing gain than MIMO flat fading channels

Minimum mean squared error equalization using a priori information

Abstract: A number of important advances have been made in the area of joint equalization and decoding of data transmitted over intersymbol interference (ISI) channels. Turbo equalization is an iterative approach to this problem, in which a maximum a posteriori probability (MAP) equalizer and a MAP decoder exchange soft information in the form of prior probabilities over the transmitted symbols. A number of reduced-complexity methods for turbo equalization have been introduced in which MAP equalization is replaced with suboptimal, low-complexity approaches. We explore a number of low-complexity soft-input/soft-output (SISO) equalization algorithms based on the minimum mean square error (MMSE) criterion. This includes the extension of existing approaches to general signal constellations and the derivation of a novel approach requiring less complexity than the MMSE-optimal solution. All approaches are qualitatively analyzed by observing the mean-square error averaged over a sequence of equalized data. We show that for the turbo equalization application, the MMSE-based SISO equalizers perform well compared with a MAP equalizer while providing a tremendous complexity reduction.