Minimum Signal Distortion Research Articles

Wavelength-selective 1/spl times/K switches using free-space optics and MEMS micromirrors: theory, design, and implementation

The design and performance of several generations of wavelength-selective 1/spl times/K switches are reviewed. These optical subsystems combine the functionality of a demultiplexer, per-wavelength switch, and multiplexer in a single, low-loss unit. Free-space optics is utilized for spatially separating the constituent wavelength division multiplexing (WDM) channels as well as for space-division switching from an input optical fiber to one of K output fibers (1/spl times/K functionality) on a channel-by-channel basis using a microelectromechanical system (MEMS) micromirror array. The switches are designed to provide wide and flat passbands for minimal signal distortion. They can also provide spectral equalization and channel blocking functionality, making them well suited for use in transparent WDM optical mesh networks.

Band-limited adaptive feedback canceller for hearing aids

An improved method for adaptively cancelling acoustic feedback in hearing aids and other audio amplification devices. Feedback cancellation is limited to a frequency band that encompasses all unstable frequencies. By limiting the bandwidth of the feedback cancellation signal, the distortion due to the adaptive filter is minimized and limited only to the unstable feedback regions. A relatively simple signal processing algorithm is used to produce highly effective results with minimal signal distortion.

Feature extraction related to bearing damage in electric motors by wavelet analysis

The purpose of this paper is to extract features from vibration signals measured from motors subjected to accelerated bearing fluting aging and to detect the effects of bearing fluting at each aging cycle of induction motors. This trending of bearing degradation is achieved by monitoring the changes in the vibration signals at various sub-band levels. This is accomplished by the application of wavelet transforms and multi-resolution analysis in order to extract information from selected frequency bands with minimum signal distortion.

ECG signal conditioning by morphological filtering

Clinically obtained electrocardiographic (ECG) signals are often contaminated with different types of noise and baseline drifting commonly occurs. In order to facilitate automated ECG analysis, signal conditioning is undoubtedly a necessity. In this paper, a modified morphological filtering (MMF) technique is used for signal conditioning in order to accomplish baseline correction and noise suppression with minimum signal distortion. Compared with existing methods for ECG signal conditioning, MMF performs well in terms of the filtering characteristics, low signal distortion ratio, low computational burden as well as good noise suppression ratio and baseline correction ratio.

Polynomial fitting + narrow reject-band f-k filtering for seismic coherent noise elimination

The paper presents a f?k filtering method to reduce coherent seismic noise. The method uses an adaptive strategy that the f?k filtering automatically adapts to lateral variations in apparent dip and amplitude of coherent noise events. We first use orthogonal polynomials to fit apparent dip and amplitude of coherent noise events. We then incorporate the instantaneous variations in apparent dip and amplitude into narrow reject-band (NRB) f?k filters which are applied in a spatially and temporally varying way across seismic traces. The method is only applied to the area where coherent noises are located and will not affect the signal that is located outside the area in the same seismic record but has the same regularity as the noise. That is, in a given window, the method removes coherent noises using the differences between noise and signal in three aspects: apparent velocity, frequency, and amplitude. The data outside the window will keep intact. The method can remove any coherent noise in prestack and poststack seismic data, which will favor following seismic processing and modification of seismic sections. The novel method has been applied to field seismic data and shows good attenuation characteristics with minimal distortion of signal.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error.

Developmental changes in the electrophysiological properties of brain stem trigeminal neurons during pattern (barrelette) formation.

In the brain stem trigeminal nuclei of rodents there is a patterned representation of whiskers and sinus hairs. The subnucleus interpolaris (SPI) contains the largest and the most conspicuous whisker patterns (barrelettes). Although neural activity plays a role in pattern formation, little is known about the electrophysiological properties of developing barrelette neurons. Here we examined the functional state of early postnatal SPI neurons during and after the consolidation of patterns by using in vitro intracellular recording techniques. After the consolidation of barrelettes [>/= postnatal day (P)4], responses to intracellular current injection consistently reflected the activation of a number voltage-dependent conductances. Most notable was a mixed cation conductance (IH) that prevented strong hyperpolarization and a large low-threshold Ca2+ conductance, which led to Ca2+ spikes and burst firing. At the oldest ages tested (P11-P14) some cells also exhibited an outward K+ conductance (IA), which led to significant delays in action-potential firing. Between P0-3, a time when the formation of barrelettes in the brain stem is still susceptible to damage of the sensory periphery, cells responded linearly to intracellular current injection, indicating they either lacked such voltage-gated properties or weakly expressed them. At all ages tested (P0-14), SPI cells were capable of generating trains of action potentials in response to intracellular injection of depolarizing current pulses. However, during the first few days of postnatal life, spikes were shorter and longer. Additionally, spike trains rose more linearly with stimulus intensity and showed frequency accommodation at early ages. Taken together, these results indicate that the electrophysiological properties of SPI neurons change markedly during the period of barrelette consolidation. Moreover, the properties of developing SPI neurons may play a significant role in pattern formation by minimizing signal distortion and ensuring that excitatory responses from sensory periphery are accurately received and transmitted according to stimulus strength.

A noise-exclusive adaptive filtering framework for removing impulse noise in digital images

A class of noise-exclusive adaptive filters for removing impulse noise from digital images is developed and analyzed in this brief. The filtering scheme is based on noise detection using a self-organizing neural network and noise excluding estimation. These filters suppress impulse noise effectively while preserving fine image details. Applications of the filters to several images show that their properties of efficient impulse noise suppression, edges and fine detail preservation, minimum signal distortion, or minimum mean square error are better than those of the traditional median-type filters.

Characterization of fiber‐optic microwave link with optoelectronic upconverter using impulse response identification system

AbstractA fiber‐optic microwave link with a monolithic integrated optoelectronic upconverter has been characterized experimentally using the impulse response identification system (IRIS). It is shown that a low‐cost optical system performs signal transmission, detection, and conversion, while introducing minimal signal distortion over that of standard radio modulation devices. This offers potential for a low‐cost solution to the problem of distribution of future microwave and millimeter‐wave signals in building for PCN and wireless LAN applications. © 1995 John Wiley & Sons, Inc.

Multichannel PC-based data-acquisition system for high-resolution EEG.

This paper describes a complete, high-performance data-acquisition system for high-resolution EEG. The system includes preamplified EEG electrodes, rigid helmets, differential instrumentation and software-controlled gain amplifiers, digitizing and control circuitry, and optical coupling to a 486 PC. Miniaturized preamplifiers mounted on individual electrodes reduce coupling to external electromagnetic fields and minimize signal distortion caused by increased and/or imbalanced electrode impedances. Electrodes are applied quickly and with minimal skin preparation, yet with high packing densities and repositioning consistent to about 1-3 mm in repeated applications. Extensive testing under realistic conditions demonstrates that the system provides superior electrical performance compared to currently available commercial systems.

Slowness adaptive f-k filtering of prestack seismic data

Frequency‐wavenumber velocity filtering is often applied to prestack seismic data for the attenuation of coherent noise. Although the process often gives excellent results, it can sometimes result in signal smoothing and distortion and poor attenuation of coherent noise. A slowness adaptive f-k filter reduces signal distortion and improves the attenuation characteristics of the filter. The technique uses a time‐ and space‐variant narrow reject‐band f-k filter. Optionally, coherent noise is compressed before application of the filter. The apparent slowness of coherent noise events is estimated using local t-x slant stacks weighted by coherence. A two‐dimensional (2-D) window is moved across the shot record, and at each point on the record slant stacks are taken through the central sample of the window. The slowness value that produces the maximum stack is assigned to the central sample of the window. In this way, an instantaneous slowness image of the shot record is produced. A one‐dimensional (1-D), high‐pass, finite‐duration impulse‐response (FIR) filter is applied in a spatially and temporally varying way across the record on the basis of the instantaneous slowness values. Before filter application, trace‐to‐trace static and amplitude effects are estimated and removed from the data. This results in compression of coherent noise and improved attenuation after filtering. The filtering process has been applied to low‐fold prestack dynamite data from the Surat Basin, Australia. The results indicate that the technique has good attenuation characteristics and produces minimal distortion of seismic signal. The process, however, is computationally expensive.

Intelligent information extraction from reflectance spectra: Absorption band positions

A multiple high‐order derivative analysis algorithm has been developed that automatically extracts absorption band positions from reflectance spectra. Absorption band positions occur where the fifth derivative of the spectrum equals zero, the fourth derivative has positive sign, and the second derivative is negative. The algorithm assumes that bands are approximately symmetric about the band center. Continuum contributions, phase angle effects, and broad low‐frequency calibration errors are suppressed. Overlapping bands with centers as close as 0.3–0.5W (full band width at half maximum intensity) can be resolved, as long as bands have comparable widths and intensities. If overlapping bands are dissimilar, band center separations of 0.6–1.0W are safer limits of resolution. Results are relatively insensitive to whether constituent bands convolve additively or multiplicatively. Spectral resolution can be moderately low, requiring only four to eight data points per W. Errors of derived band centers are <3%W for separations greater than 0.6–1.0W. For overlapping bands with widths of a few thousand cm−1 errors would be typically less than 150 cm−1 from actual band positions. The band detection algorithm is sensitive to noise, and data smoothing is required. The segment length for smoothing (number of points averaged) needs to be continually adjusted to ∼0.5W to minimize signal distortion. A spectral pattern recognition algorithm, which statistically characterizes the frequency distribution of intensity variations in a sliding segment across the spectrum, can be used to predetect the signal spectrum (low‐frequency components of the sliding intensity distributions) and to calculate approximate W (predetected W) across the spectrum using its second derivative. An intelligent control algorithm can then continuously locally adjust the segment lengths for smoothing to 0.5W (predetected W). Smooths are repeated (typically, 20–30 times) until the high‐frequency components of the sliding intensity variation distributions across the spectrum are suppressed. A single‐pass cubic spline is applied to the smoothed data. The intelligent control algorithm then applies the multiple high‐order derivative algorithm. A sliding segment sixth‐order polynomial is fit to the spectrum, with the length of the segment being continuously locally adjusted to 1.0W (predetected W) across the spectrum. Adjustment of the segment length to ∼1.0W insures that the signal spectrum is minimally distorted and that weak features are not suppressed. Derivatives are calculated for the center point of the sliding segment using the coefficients of the sixth‐order polynomial. The system has successfully extracted band positions from low‐quality (6% peak‐to‐peak noise) synthetic spectra with relatively little degradation of accuracy. Application to natural laboratory and earth‐based telescope spectra displayed good reliability and consistency. Processing is fully automated, and the same standardized procedure is followed for all spectra. No continuum removal or band modeling is needed. The automation of analysis could potentially significantly increase the efficiency and yield of information extraction, particularly for high‐rate repetitive scan laboratory and synoptic remote sensing spectroscopy applications.

Small-Aperture Focusing Chirp Transducers vs. Diffraction-Compensated Beam Compressors in Elastic SAW Convolvers

Abstmct-High performance has been achieved in SAW convolvers using diffraction-corrected multistrip beam compressors. However, two different levels of metalization are required for optimum performance. A significant simplification of device fabrication was achieved with the design of convolvers using small-aperture chirp transducers, which require only one metalization layer. A design procedure is described that makes the transducers focusing to minimize diffraction loss. Experimental results are presented, which show that performance of this new design surpasses conventional designs in several respects. I. INTRODUCTION M ONOLITHIC acoustic surface wave convolvers on YZ-LiNb03 combine high-speed signal processing capability with ruggedness, small size, and relatively low cost of the device-thanks to the simplicity of its construction. However, the intrinsic nonlinearity of the substrate material polarization, which is used to generate the mixing product of the two input signals, is low and limits the efficiency of the device. High efficiency is crucial to achieve high dynamic range and economize input power. Since the introduction of beamwidth compression [l] to boost device efficiency, the elastic convolver has been developed to high performance in several laboratories [2], [3], [4] by optimization of its various components. The aim of such optimization was to increase the device efficiency by eliminating sources of loss in the acoustic path and providing good match at all electrical ports, while tailoring the device characteristics to minimize signal distortion and suppress spurious signals [5]. This means that the convolution efficiency vs. frequency should be reasonably flat and smooth in magnitude and linear in phase over the desired bandwidth. Notably reflections of acoustic waves in the device have to be suppressed to avoid selfconvolution of one input signal. The distributed output signal has to be collected from the integrating electrode in such a way as to avoid electromagnetic propagation loss or destructive interference of various signal components due to long-line effects. By these considerations one arrives at a standard design scheme as shown in Fig. 1. Interdigital transducers, which convert the input signals, typically are unapodized to avoid

Examination of the Convolution Method for Numerical Smoothing and Differentiation of Spectroscopic Data in Theory and in Practice

General expressions have been derived for the effects of convolution on a set of experimental data, from which the noise reduction may be predicted quantitatively. From these, a new criterion is proposed for the choice of convolution function in terms of the degree, number of convolution points, and number of passes of the convolution function through the data. This criterion gives maximal noise reduction with minimal signal distortion, and is particularly applicable in resolution enhancement applications. The new criteria have been tested with experimental data.

Measurement of semiconductor–insulator interface states by constant-capacitance deep-level transient spectroscopy

Localized electronic states at the semiconductor–insulator interface adversely affect the operation of insulated-gate, field-effect devices. Characterization of interface states provides essential information for minimizing their effect through process optimization, for predicting device performance, and ultimately for microscopic identification of interface defects. This paper reviews the application of deep-level transient spectroscopy (DLTS) for characterizing interface states on metal–insulator–semiconductor capacitors, with emphasis on the constant-capacitance (CC) mode of measurement. The DLTS measurement yields both the energy distribution of interface states and their cross section for capturing free carriers. In addition, it has the versatility of being applicable to both interface and bulk defect characterization. The CC-DLTS technique offers the combined features of high sensitivity (<1×109 eV−1 cm−2), minimum signal distortion at high defect densities, high energy resolution, and the determination of dynamic properties. After a description of the measurement system and experimental procedures, the theoretical basis is developed for data reduction of majority-carrier-dominated transients for the following cases: (1) under saturating-pulse conditions and (2) with Fermi-level controlled trap occupancy. Under the first topic is included a summary of transient-current spectroscopy, and the second is illustrated with the energy-resolved DLTS technique. The presentation includes an analysis of the effect of surface generation on the DLTS measurement of interface states near the semiconductor midgap and an analysis of the limits of applicability of the transient-capaci tance mode for DLTS measurement of interface states. The techniques are illustrated with measurements of electronic defect levels at the Si–SiO2 interface.

Robust memoryless quantization for minimum signal distortion

Robust quantizers are designed for situations where there is only an incomplete statistical description of the quantizer input. The goal of the design is to closely approximate quantizer inputs by quantizer outputs without using more than a specified number of quantization levels. The exact probability distribution of the input is unknown, but this distribution is known to belong to some set <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</tex> . The primary, set <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</tex> considered is the set of all unimodal probability distributions which satisfy generalized moment constraint (e.g., mean-square value less than or equal to a constant). A quantizer is derived which minimizes over all quantizers the maximum distortion over all distributions in <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</tex> . This robust quantizer guarantees a significanfiy lower worst case distortion than the classical Gaussian-optimal quantizer, while performing nearly as well as the Gaussian-optimal quantizer when the input is, in fact, Gaussian.

Exploring the information support for speech

A well‐established feature of speech production is that talkers faced with both anticipated and unanticipated perturbations can spontaneously adjust the movement patterns of articulators such that the acoustic output remains relatively undistorted. Less clear is the nature of the underlying mechanism(s) involved. In this study we examined the production of static vowels and vowels embedded in a dynamic speech context in five subjects under normal conditions and a combined condition in which (a) the mandible was fixed via a biteblock, (b) proprioceptive information was reduced via bilateral anaesthetization of the temperomandibular joint, (c) tactile information from oral mucosa was reduced by extensive application of topical anaesthetic, and (d) auditory information was masked by white noise. Analysis of formant patterns revealed minimal distortion of the speech signal under the combined condition. These findings are unfavorable for a predictive simulation model which requires reliable peripheral information (Lindblom et al., 1979) and more in line with recent work suggesting that movement goals may be achieved by muscle collectives that behave qualitatively similar to a nonlinear vibratory system (Fowler et al., 1980; Kelso et al., 1980). [Work supported by NINCDS and BRSG.]

Three-stage adaptive noise cancellation for arbitrary signals using a source embedded pilot signal: Method 1

Two-stage noise cancellation is a recently introduced technique for cancelling noise while maintaining minimal signal distortion due to signal leakage into the noise reference. An alternative three-stage approach to noise cancellation that extends applicability from intermittent or slowly fluctuating signals to arbitrary signals is presented. This alternative is viable whenever the signal source is accessible so that a pilot signal can be additively embedded.

Three-stage adaptive noise cancellation for arbitrary signals using a source-embedded pilot signal: Method 2

Two-stage noise cancellation is a recently introduced technique for cancelling noise while maintaining minimal signal distortion due to signal leakage into the noise reference. An alternative three-stage approach to noise cancellation that extends applicability from intermittent or slowly fluctuating signals to arbitrary signals is presented. This alternative is viable whenever the signal source is accessible so that a pilot signal can be additively embedded.

The optimum processing of clipped signals: An approach based on minimum signal distortion

AbstractThe minimization of signal distortion was one approach applied successfully in the theory of optimum signal detection for arrays [3]. The processors considered operated on the input as received.In some applications it is desirable to clip the received signal before processing and the problem of optimum processing of such clipped signals then arises. Several approaches to this problem are being studied, but the present paper is concerned with that based on minimum signal distortion.