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At least 1,207 records · Page 67Linked to original sources
PubMed2002

Stability analysis for postural control in a two-joint limb system.

The stability behavior of a multi-joint limb with electrically activated muscles provides important clues for postural control of motor tasks. The stability property of the musculoskeletal system can be characterized with its eigenvalues evaluated at operating postures in the workspace. A planar arm model with shoulder and elbow joints and three pairs of antagonistic muscles was constructed in ADAMS. Stability behavior of shoulder and elbow joints was analyzed using the loci of eigenvalues in the s-plane. In the analysis of open-loop cocontraction of antagonist muscles with increasing activation from 5% to 100%, the eigenvalues of the shoulder and elbow joints were confined within the left half of the s-plane in a stripe of +/- j 0.5, and moved toward left onto the real axis. The shoulder eigenvalues were generally nearer to the imaginary axis than the elbow ones, indicating a more oscillatory behavior at the shoulder joint than that at the elbow joint. The effects of joint configuration evaluated within the workspace from 40 degrees to 110 degrees for the elbow and from 40 degrees to 120 degrees for the shoulder showed that the elbow eigenvalues were more prone to configuration changes, particularly elbow angles. We also developed a simulation paradigm for sampled data FES control systems that contain a mixture of continuous time components and sampling and hold effects. This simulation paradigm is useful for realistic simulation of local feedback controller performance.

Computer Simulation↗
PubMed2003

Evaluation of adaptive/nonadaptive filtering and wavelet transform techniques for noise reduction in EMG mobile acquisition equipment.

The myoelectric signal can be used to control many rehabilitation systems, for instance, prostheses and artificial neuromuscular electrical stimulation toward restoring movement to spinal cord injured subjects. These mobile systems are usually used in different environments and thus are being exposed to different noise levels with characteristics not completely known. In this article, three main techniques for noise reduction were evaluated: wavelet transform (WT), adaptive digital filters, and nonadaptive digital filters. The WT was used to reconstruct the signal with the components without noise information. Adaptive filters were designed using least mean square (LMS) and recursive least square (RLS) algorithms. Finite-impulse response (FIR) and infinite-impulse response (IIR) nonadaptive filters were used for comparison to both the adaptive filters and the signal reconstruction through the WT.

Algorithms↗
PubMed2004

Robust histogram construction from color invariants for object recognition.

An effective object recognition scheme is to represent and match images on the basis of histograms derived from photometric color invariants. A drawback, however, is that certain color invariant values become very unstable in the presence of sensor noise. To suppress the effect of noise for unstable color invariant values, in this paper, histograms are computed by variable kernel density estimators. To apply variable kernel density estimation in a principled way, models are proposed for the propagation of sensor noise through color invariant variables. As a result, the associated uncertainty is obtained for each color invariant value. The associated uncertainty is used to derive the parameterization of the variable kernel for the purpose of robust histogram construction. It is empirically verified that the proposed density estimator compares favorably to traditional histogram schemes for the purpose of object recognition.

Algorithms↗
PubMed2004

Machine printed text and handwriting identification in noisy document images.

In this paper, we address the problem of the identification of text in noisy document images. We are especially focused on segmenting and identifying between handwriting and machine printed text because: 1) Handwriting in a document often indicates corrections, additions, or other supplemental information that should be treated differently from the main content and 2) the segmentation and recognition techniques requested for machine printed and handwritten text are significantly different. A novel aspect of our approach is that we treat noise as a separate class and model noise based on selected features. Trained Fisher classifiers are used to identify machine printed text and handwriting from noise and we further exploit context to refine the classification. A Markov Random Field-based (MRF) approach is used to model the geometrical structure of the printed text, handwriting, and noise to rectify misclassifications. Experimental results show that our approach is robust and can significantly improve page segmentation in noisy document collections.

Algorithms↗
PubMed2004

Estimating degradation model parameters using neighborhood pattern distributions: an optimization approach.

Noise models are crucial for designing image restoration algorithms, generating synthetic training data, and predicting algorithm performance. There are two related but distinct estimation scenarios. The first is model calibration, where it is assumed that the input ideal bitmap and the output of the degradation process are both known. The second is the general estimation problem, where only the image from the output of the degradation process is given. While researchers have addressed the problem of calibration of models, issues with the general estimation problems have not been addressed in the literature. In this paper, we describe a parameter estimation algorithm for a morphological, binary, page-level image degradation model. The inputs to the estimation algorithm are 1) the degraded image and 2) information regarding the font type (italic, bold, serif, sans serif). We simulate degraded images using our model and search for the optimal parameter by looking for a parameter value for which the local neighborhood pattern distributions in the simulated image and the given degraded image are most similar. The parameter space is searched using a direct search optimization algorithm. We use the p-value of the Kolmogorov-Smirnov test as the measure of similarity between the two neighborhood pattern distributions. We show results of our algorithm on degraded document images.

Algorithms↗
PubMed2004

Recovering the missing components in a large noisy low-rank matrix: application to SFM.

In computer vision, it is common to require operations on matrices with "missing data," for example, because of occlusion or tracking failures in the Structure from Motion (SFM) problem. Such a problem can be tackled, allowing the recovery of the missing values, if the matrix should be of low rank (when noise free). The filling in of missing values is known as imputation. Imputation can also be applied in the various subspace techniques for face and shape classification, online "recommender" systems, and a wide variety of other applications. However, iterative imputation can lead to the "recovery" of data that is seriously in error. In this paper, we provide a method to recover the most reliable imputation, in terms of deciding when the inclusion of extra rows or columns, containing significant numbers of missing entries, is likely to lead to poor recovery of the missing parts. Although the proposed approach can be equally applied to a wide range of imputation methods, this paper addresses only the SFM problem. The performance of the proposed method is compared with Jacobs' and Shum's methods for SFM.

Algorithms↗
PubMed2004

Separating reflection components based on chromaticity and noise analysis.

Many algorithms in computer vision assume diffuse only reflections and deem specular reflections to be outliers. However, in the real world, the presence of specular reflections is inevitable since there are many dielectric inhomogeneous objects which have both diffuse and specular reflections. To resolve this problem, we present a method to separate the two reflection components. The method is principally based on the distribution of specular and diffuse points in a two-dimensional maximum chromaticity-intensity space. We found that, by utilizing the space and known illumination color, the problem of reflection component separation can be simplified into the problem of identifying diffuse maximum chromaticity. To be able to identify the diffuse maximum chromaticity correctly, an analysis of the noise is required since most real images suffer from it. Unlike existing methods, the proposed method can separate the reflection components robustly for any kind of surface roughness and light direction.

Algorithms↗
PubMed2004

Uncertainty modeling and model selection for geometric inference.

We first investigate the meaning of "statistical methods" for geometric inference based on image feature points. Tracing back the origin of feature uncertainty to image processing operations, we discuss the implications of asymptotic analysis in reference to "geometric fitting" and "geometric model selection" and point out that a correspondence exists between the standard statistical analysis and the geometric inference problem. Then, we derive the "geometric AIC" and the "geometric MDL" as counterparts of Akaike's AIC and Rissanen's MDL. We show by experiments that the two criteria have contrasting characteristics in detecting degeneracy.

Algorithms↗
PubMed2006

Consistency checks for particle filters.

An "inconsistent" particle filter produces--in a statistical sense--larger estimation errors than predicted by the model on which the filter is based. Two test variables are introduced that allow the detection of inconsistent behavior. The statistical properties of the variables are analyzed. Experiments confirm their suitability for inconsistency detection.

Algorithms↗
PubMed2004

Adaptive neural network control for a class of MIMO nonlinear systems with disturbances in discrete-time.

In this paper, adaptive neural network (NN) control is investigated for a class of multiinput and multioutput (MIMO) nonlinear systems with unknown bounded disturbances in discrete-time domain. The MIMO system under study consists of several subsystems with each subsystem in strict feedback form. The inputs of the MIMO system are in triangular form. First, through a coordinate transformation, the MIMO system is transformed into a sequential decrease cascade form (SDCF). Then, by using high-order neural networks (HONN) as emulators of the desired controls, an effective neural network control scheme with adaptation laws is developed. Through embedded backstepping, stability of the closed-loop system is proved based on Lyapunov synthesis. The output tracking errors are guaranteed to converge to a residue whose size is adjustable. Simulation results show the effectiveness of the proposed control scheme.

Algorithms↗
PubMed2005

Experiments with repeating weighted boosting search for optimization in signal processing applications.

Many signal processing applications pose optimization problems with multimodal and nonsmooth cost functions. Gradient methods are ineffective in these situations, and optimization methods that require no gradient and can achieve a global optimal solution are highly desired to tackle these difficult problems. The paper proposes a guided global search optimization technique, referred to as the repeated weighted boosting search. The proposed optimization algorithm is extremely simple and easy to implement, involving a minimum programming effort. Heuristic explanation is given for the global search capability of this technique. Comparison is made with the two better known and widely used guided global search techniques, known as the genetic algorithm and adaptive simulated annealing, in terms of the requirements for algorithmic parameter tuning. The effectiveness of the proposed algorithm as a global optimizer are investigated through several application examples.

Algorithms↗
PubMed2005

Wavelet-based combined signal filtering and prediction.

We survey a number of applications of the wavelet transform in time series prediction. We show how multiresolution prediction can capture short-range and long-term dependencies with only a few parameters to be estimated. We then develop a new multiresolution methodology for combined noise filtering and prediction, based on an approach which is similar to the Kalman filter. Based on considerable experimental assessment, we demonstrate the powerfulness of this methodology.

Algorithms↗
PubMed2002

Measurement of static and vibration-induced phase noise in UHF thin-film resonator (TFR) filters.

Measurements of the static phase noise and vibration sensitivity of thin-film resonator (TFR) filters operating at 640 and 2110 MHz have been made. They show that the short-term frequency instability of the filters is small compared with that induced in the oscillator signal by the sustaining stage amplifier PM (phase modulation) noise. In-oscillator measurement of filter performance under vibration indicates that fractional frequency vibration sensitivities (deltafo/fo) are on the order of several parts in 10(-9)/g. Because the percentage bandwidth and order (number of poles) of the filters was fairly constant, so was the product of the center frequency and group delay. Thus, the fractional frequency vibration sensitivity of the filters can be expressed alternatively as carrier signal phase sensitivity to vibration. The tau-omega0 product for the filters that were tested was on the order of 300 rad, so that the equivalent phase sensitivity to vibration was approximately 1 microrad/g.

Equipment Failure Analysis↗
PubMed2002

Capacitive micromachined ultrasonic transducers: next-generation arrays for acoustic imaging?

Piezoelectric materials have dominated the ultrasonic transducer technology. Recently, capacitive micromachined ultrasonic transducers (CMUTs) have emerged as an alternative technology offering advantages such as wide bandwidth, ease of fabricating large arrays, and potential for integration with electronics. The aim of this paper is to demonstrate the viability of CMUTs for ultrasound imaging. We present the first pulse-echo phased array B-scan sector images using a 128-element, one-dimensional (1-D) linear CMUT array. We fabricated 64- and 128-element 1-D CMUT arrays with 100% yield and uniform element response across the arrays. These arrays have been operated in immersion with no failure or degradation in performance over the time. For imaging experiments, we built a resolution test phantom roughly mimicking the attenuation properties of soft tissue. We used a PC-based experimental system, including custom-designed electronic circuits to acquire the complete set of 128 x 128 RF A-scans from all transmit-receive element combinations. We obtained the pulse-echo frequency response by analyzing the echo signals from wire targets. These echo signals presented an 80% fractional bandwidth around 3 MHz, including the effect of attenuation in the propagating medium. We reconstructed the B-scan images with a sector angle of 90 degrees and an image depth of 210 mm through offline processing by using RF beamforming and synthetic phased array approaches. The measured 6-dB lateral and axial resolutions at 135 mm depth were 0.0144 radians and 0.3 mm, respectively. The electronic noise floor of the image was more than 50 dB below the maximum mainlobe magnitude. We also performed preliminary investigations on the effects of crosstalk among array elements on the image quality. In the near field, some artifacts were observable extending out from the array to a depth of 2 cm. A tail also was observed in the point spread function (PSF) in the axial direction, indicating the existence of crosstalk. The relative amplitude of this tail with respect to the mainlobe was less than -20 dB.

Adipose Tissue↗
PubMed2003

Coded excitation with spectrum inversion (CEXSI) for ultrasound array imaging.

In this paper, a scheme called coded excitation with spectrum inversion (CEXSI) is presented. An established optimal binary code whose spectrum has no nulls and possesses the least variation is encoded as a burst for transmission. Using this optimal code, the decoding filter can be derived directly from its inverse spectrum. Various transmission techniques can be used to improve energy coupling within the system pass-band. We demonstrate its potential to achieve excellent decoding with very low (< 80 dB) side-lobes. For a 2.6 micros code, an array element with a center frequency of 10 MHz and fractional bandwidth of 38%, range side-lobes of about 40 dB have been achieved experimentally with little compromise in range resolution. The signal-to-noise ratio (SNR) improvement also has been characterized at about 14 dB. Along with simulations and experimental data, we present a formulation of the scheme, according to which CEXSI can be extended to improve SNR in sparse array imaging in general.

Algorithms↗
PubMedDate not supplied

Noise-resistant fitting for spherical harmonics.

Spherical harmonic (SH) basis functions have been widely used for representing spherical functions in modeling various illumination properties. They can compactly represent low-frequency spherical functions. However, when the unconstrained least square method is used for estimating the SH coefficients of a hemispherical function, the magnitude of these SH coefficients could be very large. Hence, the rendering result is very sensitive to quantization noise (introduced by modern texture compression like S3TC, IEEE half float data type on GPU, or other lossy compression methods) in these SH coefficients. Our experiments show that, as the precision of SH coefficients is reduced, the rendered images may exhibit annoying visual artifacts. To reduce the noise sensitivity of the SH coefficients, this paper first discusses how the magnitude of SH coefficients affects the rendering result when there is quantization noise. Then, two fast fitting methods for estimating the noise-resistant SH coefficients are proposed. They can effectively control the magnitude of the estimated SH coefficients and, hence, suppress the rendering artifacts. Both statistical and visual results confirm our theory.

Algorithms↗