Call for papers: Multidimensional systems and signal processing

Call for papers: Multidimensional systems and signal processing     

Optimization of systems for interperiod signal processing

The optimization methods based on the probabilistic criterion of systems for interperiod signal processing have been considered. The specified methods perform coherent rejection of passive interferences (clutter) with subsequent coherent or incoherent accumulation of rejection residues. Adaptation principles of recursive rejection filters with a priori uncertainty of correlation characteristics of clutter were proposed. The efficiency analysis of adaptive rejection filters depending on the estimation errors of clutter parameters was carried out.     

Multirate analog-digital systems for signal processing andconversion

Systems containing both analog and digital functions have been investigated with the purpose of realizing mixed-signal integrated circuits with higher levels of functionality and integration. In most cases, such mixed-signal systems are inherently multirate because of the different sampling rates employed at various stages of the system. The multirate concepts have been used for traditional applications, such as subband coding and narrowband filter design. Some unconventional applications of multirate signal processing are also emerging, both for converting between analog samples and digital words, and for realizing processing functions in an easier and more economical way than would be possible using purely digital or analog techniques. This paper reviews fundamental multirate concepts, discusses some developments in this area of integrated multirate analog-digital systems, and outlines some possible future directions for research and application     

Adaptive fuzzy systems for multichannel signal processing

Processing multichannel signals using digital signal processing techniques has received increased attention lately due to its importance in applications such as multimedia technologies and telecommunications. The objective of this paper is twofold: 1) to introduce adaptive filtering techniques to the reader who is just beginning in this area and 2) to provide a review for the reader who may be well versed in signal processing. The perspective of the topic offered here is one that comes primarily from work done in the field of multichannel (color) image processing. Hence, many of the techniques and works cited here relate to image processing with the emphasis placed primarily on filtering algorithms based on fuzzy concepts, multidimensional scaling, and order statistics-based designs. It should be noted, however, that multichannel signal processing is a very broad field and thus contains many other approaches that have been developed from different perspectives, such as transform domain filtering, classical least-square approaches, neural networks, and stochastic methods, just to name a few. We present a general formulation based on fuzzy concepts, which allows the use of adaptive weights in the filtering structure, and we discuss different filter designs. The strong potential of fuzzy adaptive filters for multichannel signal applications, such as color image processing, is illustrated with several examples     

Embedded software in real-time signal processing systems: designtechnologies

The increasing use of embedded software, often implemented on a core processor in a single-chip system, is a clear trend in the telecommunications, multimedia, and consumer electronics industries. A companion paper (Paulin et al., 1997) presents a survey of application and architecture trends for embedded systems in these growth markets. However, the lack of suitable design technology remains a significant obstacle in the development of such systems. One of the key requirements is more efficient software compilation technology. Especially in the case of fixed-point digital signal processor (DSP) cores, it is often cited that commercially available compilers are unable to take full advantage of the architectural features of the processor. Moreover, due to the shorter lifetimes and the architectural specialization of many processor cores, processor designers are often compelled to neglect the issue of compiler support. This situation has resulted in an increased research activity in the area of design tool support for embedded processors. This paper discusses design technology issues for embedded systems using processor cores, with a focus on software compilation tools. Architectural characteristics of contemporary processor cores are reviewed and tool requirements are formulated. This is followed by a comprehensive survey of both existing and new software compilation techniques that are considered important in the context of embedded processors     

Simulation and implementation tools for signal processing andcommunication systems

It is now possible to move easily from a top-level simulation model of a system toward its implementation. While this path is seamless and nearly complete for the digital implementation, gaps still exist for the implementation of RF and optical portions of communication systems. The author describes the state of the art in waveform (or functional) level simulation tools for communication and signal processing systems with links to digital implementation     

Transmission and signal processing techniques for gigabit lightwave systems

The technology of optical-fiber transmission systems has advanced rapidly within recent years; a number of laboratories having reported gigabit transmission over 100-km spans. These developments have placed increasing emphasis on the associated signal processing functions such as timing extraction and regeneration. This paper will review laser, fiber, and receiver requirements for high-speed systems and describe two recent lightwave transmission experiments featuring distributed feedback lasers, low-loss dispersion-shifted fiber, germanium avalanche photodiode receivers, and gallium arsenide logic devices.     

A review of median filter systems for analog signal processing

This paper presents a review of existing analog implementations of the median and other ranked-order filter operations. The basic properties of median signal processing are first reviewed. Different analog median filter architectural approaches and implementations, introduced by several authors, are then discussed. These include filters based on analog delay lines and either nonlinear selection networks or ramp voltage generators. The Linear-Median Hybrid filter concept is presented and two examples of analog circuit implementations are given. Finally, a neural network approach is discussed.     

Feature - Multidimensional systems and signal processing: Good theory for good practice

The subject of multidimensional systems, as originally conceived, is concerned with a mathematical framework for tackling a broad range of paradigms whose analysis or synthesis require the use of functions and polynomials in either several complex or real variables. Its applications, which may range from the processing of spatial and temporal signals of diverse physical origin to the design of linear continuous-discrete multidimensional control systems, are already plentiful. This paper aims to promote interaction between a broad spectrum of scientists and engineers through clear exposition and interpretation of fundamentals, albeit a daunting task, so that complex theoretical results become useful to practitioners in distinct but related disciplines. The expanding arena of theory and applications of the original aims and scopes attest to the importance and vitality of the subject-matter.     

Digital signal processing techniques in Nyquist-WDM transmission systems

In single-carrier wavelength-division multiplexing (WDM) systems, the spectral efficiency can be increased by reducing the channel spacing through digital signal processing (DSP). Two major issues with using tight filtering are cross talk between channels and inter-symbol interference (ISI) within a channel. By fulfilling the Nyquist criterion, Nyquist spectral-shaped WDM systems can achieve narrow channel spacings close to the symbol rate \((\hbox {R}_{\mathrm{S}})\) with negligible cross talk and ISI. In principle, DSP can generate any signals with arbitrary waveforms and spectrum shapes. However, the complexity of DSP is limited by its cost and power consumption. It is necessary to optimize the DSP to achieve the required performance at a minimum complexity. In this paper, we first introduced the background of digital signal processing for Nyquist spectral shaping in optical fiber WDM systems. Then, we investigated the use of digital finite impulse response (FIR) filters to generate Nyquist-WDM 16-ary quadrature amplitude modulation (16QAM) signals with the raised-cosine (RC) and root-raised-cosine (RRC) shape spectra. The system performance of both the RC and RRC spectra is also examined. Moreover, we explored the various methods to reduce digital-to-analog converter (DAC) sampling speed, such as using super-Gaussian electrical filters (E-filter) and spectral pre-emphasis. We also discussed receiver-side matched filter design for Nyquist-WDM receiver optimization.