Effects Of Filter Parameters Research Articles

Split-Spectrum Processing with Raised Cosine Filters of Constant Frequency-to-Bandwidth Ratio for L(0,2) Ultrasonic Guided Wave Testing in a Pipeline

Ultrasonic guided wave (UGW) nondestructive testing suffers from poor signal interpretation accuracy caused by the coherent noise that is related to dispersion, multi-mode and mode conversion. In order to split the L(0,2) UGW from the coherent noise, split-spectrum processing with raised cosine filters of constant frequency-to-bandwidth ratio (FBR-RC-SSP) is proposed. With the advantages of time domain resolution and frequency domain split, FBR-RC-SSP is studied based on time-frequency analysis using the chirplet transform, and the effects of filter parameters on signal-to-noise ratio gain (SNRG) and defect-to-coherent noise gain (DCRG) are explained. The excellent effects of eliminating the coherent noise and improving the signal resolution in FBR-RC-SSP are reported by the validation of synthesized, simulated and experimental UGW signals, of which the average SNRG and DCRG are 22.92% and 23.71% higher than those of traditional SSP using Gaussian filters, and it has the potential to locate and characterize defects in further UGW testing research.

The Effect of Filter Parameters on the Accuracy of ECG Signal Measurement

The problem of reducing ECG measurement error by processing ECG signals with physiological and electrical noise is considered. Recommendations are given for selecting the filter passband optimal for minimizing the ECG signal measurement error and, as a consequence, improving the accuracy of measurement of its amplitude and time parameters. The effectiveness of application of a band-pass filter is corroborated by the results of processing of experimental ECG signals.

Design of Multiple Feedback Control Loops for a Single-phase Full-bridge Inverter Based on Stability Considerations

Single-phase inverters employ LC filters for the purpose of reducing pulse-width modulation harmonics. The drawback of LC filter is its stability problem at resonance frequency. Passive damping offers simple and reliable solution, but it decreases the overall system efficiency. Active damping is lossless and provides flexibility of controlling the damping performance; however, it is sensitive to parameters variation. This article presents stability analysis of a single-phase full-bridge inverter to improve dynamic performance and stability. Design of LC filter is carried out considering both undamped and damped structures. The effect of filter parameters on pole-zero locations of the inverter is presented, and variation of the phase margin over a wide range of parameters variation is examined. Active damping using closed-loop current control of the full-bridge inverter to mitigate the resonance oscillation is designed and compared with passive damping. The disturbance rejection via dynamic stiffness with and without active damping is examined to justify the proposed current controller. Simulation and experimental results are presented to validate the effectiveness of the proposed design. It is found that the proposed control of the inverter provides excellent voltage regulation with low total harmonic distortion and ensures good performance and robust stability under parameters variation.

Effect of filter parameters on enhanced performance of highly nonlinear fiber-based all optical thresholding

A principle-of-concept demonstration about the effect of filter parameters on the output performance of a highly nonlinear fiber-based all optical thresholding technique (OTT) is proposed. The center wavelength, bandwidth, and rejection parameters of an optical bandpass filter (OBPF) used in fiber-based OTT are discussed. Carefully adjusting each parameter of the OBPF allows a steeper transforming characteristic of optical thresholding, and a fourth-order polynomial power transfer function is achieved, which is the steepest thresholding curve ever reported. To the best of our knowledge, this is the first demonstration of fiber-based OTT focusing on OBPF parameters, which makes the thresholder more flexible and allows customization of thresholding performance to meet requirements in various systems.

Effect of filter parameters on the phase noise of RF MEMS tunable filters employing shunt capacitive switches

The effect of filter parameters on the phase noise of RF MEMS tunable filters employing shunt capacitive switches is investigated in this article. It is shown that the phase noise of a tunable filter is dependent on the input power, fractional bandwidth, filter order, resonator quality factor, and tuning state. Phase noise is higher for filters with smaller fractional bandwidth. In filters with high fractional bandwidth (>3%), phase noise increases as the input power approaches the power-handling capability of the filter. In filters with smaller bandwidths, phase noise increases with input power upto a threshold level of input power, but begins to decrease thereafter. The unloaded quality factor of the filter has a noticeable effect on the phase noise of filters with narrow bandwidths. The phase noise changes with the filter tuning state and is maximum when all the switches are in the up-state position. It is also shown that the phase noise increases with the filter order, due to increase in the number of noisy elements in the filter structure. This article provides a methodology to evaluate the phase noise of a tunable filter and proves that RF MEMS filters are suitable for high performance applications without considerable phase-noise penalty. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.

A multidimensional nonlinear edge-preserving filter for magnetic resonance image restoration

The paper presents a multidimensional nonlinear edge-preserving filter for restoration and enhancement of magnetic resonance images (MRI). The filter uses both interframe (parametric or temporal) and intraframe (spatial) information to filter the additive noise from an MRI scene sequence. It combines the approximate maximum likelihood (equivalently, least squares) estimate of the interframe pixels, using MRI signal models, with a trimmed spatial smoothing algorithm, using a Euclidean distance discriminator to preserve partial volume and edge information. (Partial volume information is generated from voxels containing a mixture of different tissues.) Since the filter's structure is parallel, its implementation on a parallel processing computer is straightforward. Details of the filter implementation for a sequence of four multiple spin-echo images is explained, and the effects of filter parameters (neighborhood size and threshold value) on the computation time and performance of the filter is discussed. The filter is applied to MRI simulation and brain studies, serving as a preprocessing procedure for the eigenimage filter. (The eigenimage filter generates a composite image in which a feature of interest is segmented from the surrounding interfering features.) It outperforms conventional pre and post-processing filters, including spatial smoothing, low-pass filtering with a Gaussian kernel, median filtering, and combined vector median with average filtering.