Signal Processing for Biometric Systems [DSP Forum]

This IEEE signal processing magazine (SPM) forum discuses signal processing applications, technologies, requirements, and standardization of biometric systems. The forum members bring their expert insights into issues such as biometric security, privacy, and multibiometric and fusion techniques. The invited forum members are Prof. Anil K. Jain of Michigan State University, Prof. Rama Chellappa of the University of Maryland, Dr. Stark C. Draper of theUniversity of Wisconsin in Madison, Prof. Nasir Memon of Polytechnic University, and Dr. P. Jonathon Phillips of the National Institute of Standards and Technology. The moderator of the forum is Dr. Anthony Vetro of Mitsubishi Electric Research Labs, and associate editor of SPM.     

扫描探针显微镜在石墨烯研究中的应用

石墨烯是近年来材料、电子和纳米科学中的热门研究课题之一。石墨烯独特的二维结构和原子尺度的平整性使其特别适合利用扫描探针显微镜进行深入研究。利用扫描探针显微镜可以对石墨烯样品的表面的电学、力学和光学等性质进行细致的表征;同时,还可以对石墨烯进行精细的纳米尺度微加工。本文以各种扫描探针显微镜为基础,综述了扫描探针显微镜在石墨烯研究中起到的重要的表征和加工作用。同时,还详细介绍了石墨烯表面研究中的最新进展,并对扫描探针显微镜在石墨烯研究中所具有的潜力进行了探讨。     

Reading to learn to do

It is pointed out that workplace reading primarily involves reading to do or reading that specifies action, as opposed to reading to learn or reading that centers on a topic as in a classroom. The author's development of reading to learn to do materials or tutorials that help users both to use a program and to learn is discussed. Her comparison with other research and her guidelines for developing effective tutorials provide help for the technical communicator's design of tutorials and have implications for the educator's design of assignments     

Digital image restoration

The article introduces digital image restoration to the reader who is just beginning in this field, and provides a review and analysis for the reader who may already be well-versed in image restoration. The perspective on the topic is one that comes primarily from work done in the field of signal processing. Thus, many of the techniques and works cited relate to classical signal processing approaches to estimation theory, filtering, and numerical analysis. In particular, the emphasis is placed primarily on digital image restoration algorithms that grow out of an area known as “regularized least squares” methods. It should be noted, however, that digital image restoration is a very broad field, as we discuss, and thus contains many other successful approaches that have been developed from different perspectives, such as optics, astronomy, and medical imaging, just to name a few. In the process of reviewing this topic, we address a number of very important issues in this field that are not typically discussed in the technical literature     

Quality matters, especially in sharing knowledge [From the Editor]

These days, all it takes is a few clicks of the mouse for a person to access massive amounts of information and data through Web pages, blogs, or social-centric Web sites. This easy-to-access and fast-to-find information is what makes the era we live in a special one. But with all this advancements comes the question of quality . Does the shared knowledge have high quality? What sources can one rely on to access quality knowledge? This is where publications such as IEEE Signal Processing Magazine (SPM) play an important role. Signal processing as indicated by our new editor-in-chief, Dr. Li Deng, is going through a transformation from focusing on low-level signals such as waveforms to dealing with semantic and human-centric signals. This signal processing transformation has to be accompanied by a metamorphosis in how the community exchanges high-quality knowledge and how the community members learn from each other.     

A printer model using signal processing techniques

An accurate printer model that is efficient enough to be used by halftoning algorithms is proposed. The proposed signal processing model (SPM) utilizes a physical model to train adaptive linear combiners (ALCs), after which the average exposure of each subpixel for any input pattern can be calculated using the optimized weight vector. The SPM can be used to model multi-level halftoning and resolution enhancement, as well as traditional halftoning. The SPM is comprised of a single ALC layer followed by a peak-to-average ratio (PAR) correction layer, which serves to produce a PAR of less than 1.5 in the modeled exposure. The PCN (PAR correction network) employs one ALC/pixel and exploits the physics governing the characteristics of exposure in small regions. A relatively small number of training patterns suffices to train the SPM.     

On the convergence of traffic measurement and queueing analysis: astatistical-matching and queueing (SMAQ) tool

The analytical tool developed by the authors provides a general solution technique for integration of traffic measurement and queueing analysis. The frequency-domain approach is used to combine the advanced techniques in two areas: signal processing and queueing analysis. Essentially, signal processing techniques are used to obtain the steady-state and second-order statistics of a traffic stream. We propose a new programming method for the construction of a special class of Markov chains to statistically match with each given traffic stream (or superposition of heterogeneous traffic streams). The analytical queueing solutions can therefore be obtained by the folding-algorithm based on Markov chain input modeling. Comprehensive numerical examples show the great potential of the statistical-matching and queueing (SMAQ) tool to solve measurement-based traffic management issues     

Basic aspects concerning the event-synchronous interference canceller

The adaptive noise canceller (ANC) is a commonly used linear system method for noise reduction in cases where the disturbing noise can be separately recorded (reference signal) and is not correlated with the signal of interest. In case of a periodic disturbing signal, special solutions are described in literature. Problems, however, arise when the propagation of the noise from the source to the recording sensors passes nonlinear structures. An ANC modification proposed for this case by Strobach et al. and applied by several other researchers, thus, uses an artificial reference signal, based on event triggered averaging of segments of the recorded wanted (but disturbed) signal in order to obtain a template for the repetitive distortion sequence and to construct the artificial reference signal. The effect of the averaging and the error introduced by this approximation of the real disturbing signal was not addressed in literature until now, thus, this paper presents some basic theoretical considerations on this topic. Methods are demonstrated in simulations and real biosignal processing, and application aspects are discussed.     

Radio resource management and protocol engineering for IEEE 802.16 [Guest Editorial]

The special section features six articles that focus on radio resource management issues in IEEE 802.16/WiMAX-based broadband wireless systems. This guest editorial discusses the major issues pertaining to the topic and summarizes the articles included in this section.     

Sunny San Diego hosts ICIP 2008 [Conference Spotlight]

The 15th International Conference on Image Processing (ICIP) will be held at the Convention Center in downtown San Diego, California, 12-15 October 2008. ICIP is the world?s premier conference focused on image processing and its applications. The conference will feature internationally reputed speakers, tutorials, exhibits, and over 50 lectures and poster sessions, including six special oral sessions. As a new concept to ICIP, we will be organizing a one-day workshop, "Multimedia Information Retrieval: New Trends and Challenges," which will feature invited talks, oral, and poster presentations. We hope that the workshop format will (in the future) enable the showcasing of new themes as well as nostalgic ones.     

Space-time adaptive processing: a knowledge-based perspective for airborne radar

This article provides a brief review of radar space-time adaptive processing (STAP) from its inception to state-of-the art developments. The topic is treated from both intuitive and theoretical aspects. A key requirement of STAP is knowledge of the spectral characteristics underlying the interference scenario of interest. Additional issues of importance in STAP include the computational cost of the adaptive algorithm as well as the ability to maintain a constant false alarm rate (CFAR) over widely varying interference statistics. This article addresses these topics, developing the need for a knowledge-based (KB) perspective. The focus here is on signal processing for radar systems using multiple antenna elements that coherently process multiple pulses. An adaptive array of spatially distributed sensors, which processes multiple temporal snapshots, overcomes the directivity and resolution limitations of a single sensor.     

On Sampling of Band-Limited Signals Associated With the Linear Canonical Transform

Sampling is one of the fundamental topics in the signal processing community. Theorems proposed under this topic form the bridge between the continuous-time signals and discrete-time signals. Several sampling theorems, which aid in the reconstruction of signals in the linear canonical transform (LCT) domain, have been proposed in the literature. However, two main practical issues associated with the sampling of the LCT still remain unresolved. The first one relates to the reconstruction of the original signal from nonuniform samples and the other issue relates to the fact that only a finite number of samples are available practically. Focusing on these issues, this paper seeks to address the above from the LCT point of view. First, we extend several previously developed theorems for signals band-limited in the Fourier domain to signals band-limited in the LCT domain, followed by the derivation of the reconstruction formulas for finite uniform or recurrent nonuniform sampling points associated with the LCT. Simulation results and the potential applications of the theorem are also proposed.      

Single nucleotide polymorphism data analysis - State-of-the-art review on this emerging field from a signal processing viewpoint

The basic structural units of the genome are nucleotides. A single nucleotide polymorphism (SNP) is a mutation at a single nucleotide position. This paper discusses several major problems in SNP data analysis and review some existing solutions in this work. Generally speaking, a rich set of SNP analysis problems are cast in the signal processing framework. Our objective is to offer a state-of-the art review on this topic from a signal processing viewpoint so that researchers in the signal processing field can grasp the important domain knowledge to overcome the barrier between the two fields     

基于DSP的小波阈值去噪算法的实现

小波去噪是信号处理领域中的热点与前沿课题。阐述了小波去噪的基本原理和方法,利用TMS320F2812 DSP高速的运算能力、强大的实时处理能力等特点,在DSP上实现小波阈值去噪算法,为小波去噪提供了实时处理平台。采用软阈值函数和tein无偏风险阈值2t（rigrure规则）对噪声污染信号进行小波阈值去噪处理,实验发现,该法可以很好的去除噪声,满足信号去噪的光滑性和相似性准则。     

宽带数字信号处理及其在电子战中的应用

宽带数字信号处理是电子战研究的主题之一。相对于窄带而言,宽带会导致数字动态、灵敏度、多信号处理等变差。针对这些问题,结合现代先进的电子技术,介绍了宽带数字信号处理中的宽带采集、阵列处理、数字信道化以及数字储频干扰等技术,分析了宽带对这些技术的影响,探讨了宽带数字信号处理技术在电子战中的应用及发展方向,为研究数字信号处理技术的工程师提供有益的参考。     

Brain-Computer Interfaces [from the guest editors]

The nine articles in this special issue focus on brain-computer interfaces. The authors contributing to this special issue represent researchers who have one foot in the signal processing and machine learning community and one foot in the world of the neurosciences. The contributed articles thus represent a marriage of the two disciplines, though with an emphasis on the signal processing aspects and challenges.     

基于AD1954的数字音响处理系统的设计

介绍了音频信号处理专用DSP芯片AD1954的主要特性及其数字音频信号处理流程。在此基础上,提出一种以AD1954为核心的数字音响处理系统设计方案。利用AD1954专业的数字信号处理能力,实现了均衡、延时、分频等多种复杂的音频处理,利用单片机与AD1954的SPI端口之间的串行通信,实现对AD1954的控制。本系统能适应音响工程的应用要求。     

Analysis of the Electromagnetic Signals of the Human Brain: Milestones, Obstacles, and Goals

Measuring the functioning of the human brain is one of the most formidable scientific/engineering endeavors ever undertaken. It is difficult to extract information about any particular processing function from brain electromagnetic signals (BEMS) since, at any instant, only a small fraction of the brain's hundreds of simultaneously active major systems might be performing processing related to the function being studied. With recent developments, a new era of research is dawning based on an interdisciplinary approach in which advanced signal processing methods are focused on increasingly more specific neuroanatomical, neurophysiological, and neuropsychological research questions and clinical applications. This brief review highlights the major accomplishments of the last several decades in human BEMS analysis and discusses obstacles to progress. Five main topics are addressed: 1) the historical problem of developing a computerized expert clinical electroencephalogram (EEG) system; 2) advances in signal processing methods, including primary analysis, feature extraction, and statistical hypothesis testing and pattern classification; 3) integrated computing systems for BEMS analysis; 4) biophysical, basic science, practical and conceptual obstacles to progress; and 5) the long-term goal of developing a device for measuring the functional integrity of major neural systems, and the related topic of neurocybernetics. Cutting-edge issues discussed include measurement and modeling of nonstationary event-related signals, characterization of spatial processes, single-trial signal detection, location of the sources of scalp-recorded field distributions, and studies of the functional significance of BEMS.     

Looking Forward: New Ideas, New Opportunities

The editor in chief discusses upcoming special issues, topic trends in multimedia, article submissions in 2007, and our volunteers' efforts.     

基于数字信号处理器DSP的SPM研究

本文以TI公司的TMS320C54xDSP为核心，介绍了DSP-SPM全数字化系统。文章首先指出目前国产扫描探针显微镜存在智能化及集成度不高、PID参数调节不方便、成本高等不足。进而引入数字信号处理器(Digital Signal Processor DSP)，介绍了TMS320C54x DSP的特点及其开发工具；然后给出了DSP-SPM系统的框图及DSP算法；文章最后还简单介绍了利用’54X的HPI(Host Port Interface)与PC机并口通讯的情况。