Phase Finite Impulse Response Filters Research Articles

To Bag or Not to Bag? How AudioMoth-Based Passive Acoustic Monitoring Is Impacted by Protective Coverings

Bare board AudioMoth recorders offer a low-cost, open-source solution to passive acoustic monitoring (PAM) but need protecting in an enclosure. We were concerned that the choice of enclosure may alter the spectral characteristics of recordings. We focus on polythene bags as the simplest enclosure and assess how their use affects acoustic metrics. Using an anechoic chamber, a series of pure sinusoidal tones from 100 Hz to 20 kHz were recorded on 10 AudioMoth devices and a calibrated Class 1 sound level meter. The recordings were made on bare board AudioMoth devices, as well as after covering them with different bags. Linear phase finite impulse response filters were designed to replicate the frequency response functions between the incident pressure wave and the recorded signals. We applied these filters to ~1000 sound recordings to assess the effects of the AudioMoth and the bags on 19 acoustic metrics. While bare board AudioMoth showed very consistent spectral responses with accentuation in the higher frequencies, bag enclosures led to significant and erratic attenuation inconsistent between frequencies. Few acoustic metrics were insensitive to this uncertainty, rendering index comparisons unreliable. Biases due to enclosures on PAM devices may need to be considered when choosing appropriate acoustic indices for ecological studies. Archived recordings without adequate metadata may potentially produce biased acoustic index values and should be treated cautiously.

Minimum phase finite impulse response filter design

The design of minimum phase finite impulse response (FIR) filters is considered. The study demonstrates that the residual errors achieved by current state-of-the-art design methods are nowhere near the smallest error possible on a finite resolution digital computer. This is shown to be due to conceptual errors in the literature pertaining to what constitutes a factorable linear phase filter. This study shows that factorisation is possible with a zero residual error (in the absence of machine finite resolution error) if the linear operator or matrix representing the linear phase filter is positive definite. Methodology is proposed able to design a minimum phase filter that is optimal—in the sense that the residual error is limited only by the finite precision of the digital computer, with no systematic error. The study presents practical application of the proposed methodology by designing two minimum phase Chebyshev FIR filters. Results are compared to state-of-the-art methods from the literature, and it is shown that the proposed methodology is able to reduce currently achievable residual errors by several orders of magnitude.

Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise

This study describes an iterative learning approach to the active control of machinery noise with high autocorrelation properties. In contrast to typical active noise control solutions, which work by adapting the transfer function of the controller, in the iterative learning control one adapts the control signal itself. Special care was taken to develop a generic solution that can handle different sorts of secondary path models including very long and non-minimum phase finite impulse response filters. To achieve that, the authors used spectral factorisation and exploit the fact that, for non-minimum phase systems, a stable inverse can be constructed if the causality constraint is relaxed and later restored by taking advantage of the periodicity of the attenuated signal. The resulting controller can be efficiently implemented on a sample-to-sample calculation basis. The behaviour and the performance of the proposed scheme are studied using computer simulations and real-world experiments on noises from an electric transformer and functional magnetic resonance imaging device. The proposed solution was also compared to normalised feedforward filtered-X least mean squares algorithm and performed much better in terms of attenuation, convergence, and robustness.

Sparse Finite Impulse Response Low Pass Filter Design using Improved Firefly Algorithm

In this work, optimal sparse linear phase Finite impulse response filters are designed using swarm intelligence-based Firefly optimization algorithm. Filters are designed to meet the desired specification with fixed and variable sparsity. The objective function is formulated consisting of three parameters, i. e., maximum passband ripple, maximum stopband ripple and stopband attenuation. The effectiveness of the proposed method is evaluated in two stages. In first stage, the designed filters have been compared with non- sparse in terms of deviation in their specification. The Comparative analysis depicts that the proposed approach of sparse linear phase FIR filter design method performs better than the conventional methods without significantly deviating from the desired specification. The proposed designed filter is then implemented on xilinx ISE14.7(Vertex7) design environment and their performance is compared in terms of time delay, resource utilizaion and frequency of operation. In the second stage, designed sparse FIR filters are compared with earlier state of art sparse FIR filters design techniques.

Variant of the charged system search algorithm for the design of optimal linear phase finite impulse response filters

ABSTRACT Digital signal filtering is one of the prime area which is frequently used in practical applications. In the class of digital filters, the prominent filters include – filters with finite impulse response (FIR) and filters with infinite impulse response (IIR). Low pass, high pass, band pass and band stop filters are the different types of filters that are currently employed for carrying out filtering actions. Filters are used for practical applications to reduce the noise incurred while processing the signals received, whether it may be an audio signal, video signal, bio-medical signal and so on. The key features for the design of filters include the optimization of coefficients and in turn the design of coefficients is based on attaining maximum stop band attenuation with less ripple rates. This paper proposes the soft computing based wavelet concept being introduced in the charged system search algorithm at the updation process. The scaling factor in the updation equation is implemented with a wavelet introduced to improve the exploration and exploitation capability of the algorithm. This introduction of wavelet into the algorithm results in faster convergence of the algorithm and proves its effectiveness in comparison with that of the other approaches as available in the literature.

Simultaneous measurement of transverse load and temperature using hybrid structured fiber-optic Fabry\u2013Perot interferometer

We experimentally demonstrated a novel fiber-optic hybrid structured Fabry–Perot interferometer with special air-cavity for simultaneous measurement of transverse load and temperature. By the linear phase finite impulse response filters, the transverse load sensitivities of the air-cavity and the silica-cavity are 1272.71 pm/N and −53.07 pm/N, respectively, and temperature sensitivities of the air-cavity and silica-cavity are 1.1 pm/°C and 14 pm/°C. Thus, the different sensitivities of silica-cavity and air-cavity to transverse load and temperature indicate that such a structure can be used to simultaneously measure transverse load and temperature.

基于特征向量的线性相位FIR滤波器设计

本文将线性相位FIR滤波器的设计表示成一个实对称正定矩阵的特征问题。根据求解该矩阵的最小特征值所对应的特征向量来确定滤波器的系数。通过在通带取平均的方法，避免了参考频率的设定问题。仿真结果表明，该方法提高了特征滤波器法的设计性能。 In this paper, the design of a linear phase finite impulse response filter is formulated as an eigen problem of a real, symmetric, positive-definite matrix. The unknown filter coefficients can be obtained by calculating the eigenvector corresponding to the minimum eigenvalue of the matrix. The modified method does not need a reference frequency point for normalization as done in traditional eigenfilters. Instead, average over the passband is carried out. Simulations show that the modified method leads to improved design performance.

Spectral Graph Wavelets and Filter Banks With Low Approximation Error

We propose filter banks in the graph spectral domain, where each filter is defined by a sum of sinusoidal waves. The main advantages of these filter banks are that (a) they have low approximation errors even if a lower-order shifted Chebyshev polynomial approximation is used, (b) the upper bound of the error after the pth order Chebyshev polynomial approximation can be calculated rigorously without complex calculations, and (c) their parameters can be efficiently obtained from any real-valued linear phase finite impulse response filter banks in regular signal processing. The proposed filter bank has the same filter characteristics as the corresponding classical filter bank in the frequency domain and inherits the original properties, such as tight frame and no DC leakage. Furthermore, their approximation orders can be determined from the desired approximation accuracy. The effectiveness of our approach is evaluated by comparing them with existing spectral graph wavelets and filter banks.

Two-Step Optimization Approach for the Design of Multiplierless Linear-Phase FIR Filters

Deterministic tree search algorithms for the design of multiplierless linear phase finite impulse response filters are generally time consuming. Many researches therefore focus on how to restrict the number of discrete values assigned to each coefficient during a tree search. In this paper, a two-step tree search algorithm is proposed. In the first step, a polynomial-time tree search algorithm where each coefficient is fixed to a single one discrete value is introduced. Since the synthesis of large coefficients is dominant in the hardware cost over small coefficients, in the second step optimization, the small coefficients obtained in the first step is kept unaltered and the large coefficients are further divided into several groups and the coefficients are optimized group by group alternatingly. Such a two-step search strategy maximally utilizes the limited computational resources and can achieve lower hardware cost design in a shorter design time, compared with existing algorithms.

A comparison of LTE channelizers implemented with linear phase m-path recursive filters and FIR filters

Cell sites repeaters may receive a composite signal containing a mix of long term evolution channels with bandwidths of 5, 10, 15, and 20 MHz and be required to rearrange the frequency plan of the channels or to drop and insert specific channels prior to transmitting the altered composite signal. The straight forward approach to this task is to down-convert, and down-sample each channel in the mix and then up-sample and up-convert and merge the new traffic mix. The filters applied to the up and down conversion task as well as the up and down sampling task would likely be linear phase finite impulse response (FIR) filters because of the ease with which the resampling task can be embedded in the filtering task. We present an alternate filter structure formed from linear phase recursive filters and compare their performance and computational complexity with their FIR filter counterparts. We show that the recursive filter version of the channel extractor requires significantly few arithmetic operations and actually outperforms the non-recursive version as demonstrated by the error vector magnitude of the two options.

Seeker optimisation algorithm: application to the design of linear phase finite impulse response filter

This study presents a novel seeker optimisation algorithm (SOA) for the design of linear phase finite impulse response low pass, high pass, band pass and band stop digital filters. A new fitness function has been adopted in order to improve the stop band attenuation, stop band ripple and to have an accurate control on the transition width. A comparison of simulation results reveals the optimisation efficacy of SOA in terms of error fitness value, stop band attenuation and stop band ripple over the prevailing optimisation techniques reported in recent literatures.

Differential Evolution with Wavelet Mutation in Digital Finite Impulse Response Filter Design

This paper proposes one novel algorithm called differential evolution with wavelet mutation for the optimal design of linear phase finite impulse response filters. For comparative performance study, the Parks–McClellan algorithm and some evolutionary algorithms like the real coded genetic algorithm, conventional particle swarm optimization, and conventional differential evolution have also been applied.

Realization of reduced-delay finite impulse response filters for audio applications

This article aims to present a development of reduced-delay finite impulse response digital filters with amplitude requirements using equiripple passband, peak constrained least squares stopbands, and nearly constant group delay in passband for real-time applications. The filter length, passband and stopband frequencies, ripples, and attenuation are specified for realizations. The obtained results of realized filters have group delays with a reduction of about 12–22% in passband compared to the existing linear phase finite impulse response filters for audio applications.

Mobile speed estimation for TDMA-based hierarchical cellular systems

A new algorithm is presented for estimating mobile speed for handoff in hierarchical cellular systems. The proposed algorithm is based on normalized autocorrelation values of received signals to estimate mobile speed; it contains six steps. First, the instantaneous power of the received baseband signal is calculated to remove the offset and data/speech information-bearing signals, while keeping the Doppler information. Second, the calculated power signal is filtered using a low-pass linear phase finite impulse response filter to suppress interference and noise. Third, the filtered power signal is decimated to ease the computational burden, while the decimation factor is properly chosen to avoid aliasing. Fourth, autocorrelation values of the decimated filtered power signals are calculated on shifting by to suppress the slot burst frequency interference. Fifth, the calculated autocorrelation values are normalized to suppress the power fluctuation of the received signals. Finally, the normalized autocorrelation values are compared with thresholds to estimate mobile speed. The simulation results indicate that the new algorithm works very well for both nondispersive channels and dispersive channels to distinguish fast and slow moving mobiles. The method has very low latency, with results being available typically within 1 s after communication is established, and it can report estimation result every second or less. The algorithm has been implemented by software code into Nortel's base-station radios and tested in Nortel's wireless communications labs.

Complex eigenfilter design of arbitrary complex coefficient FIR digital filters

The real eigenfilter approach is extended to complex cases for designing arbitrary complex finite impulse response (FIR) filters. By minimizing a quadratic measure of the error in the passband and stopband, a complex eigenvector of an appropriate complex, Hermitian symmetric, and positive-definite matrix is computed to get the filter coefficients. Several arbitrary magnitude and phase FIR filters, such as multiple passband complex filters and staircase-delay allpass phase equalizers, can be easily designed by this approach. This method can be easily extended to design 2-D complex FIR filters. If an appropriate iterative process is used, equiripple filters in the complex Chebyshev sense can be obtained. Several numerical design examples demonstrate the usefulness of the approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

2-D generalized MFIR filters

An efficient structure for 2-D linear phase FIR (finite-impulse response) filters is introduced. The structure is the 2-D counterpart of the 1-D MFIR (multiplicative FIR) filters. It is shown that this structure is capable of satisfying tight specifications with a significantly reduced number of coefficients. The performance improves for tighter specifications with centered transition bands. The filter coefficients are obtained by minimizing an l/sub p/ error function. It is shown that the optimization problem is readily broken up into a set of simpler subproblems. For the special case of p=2, these subproblems reduce to simple matrix inversions. Increasing the filter order does not affect the problem complexity since it only requires an increase in the number of matrix inversions needed. Examples illustrating the capabilities of this structure and comparisons with other approaches are given. >

A new efficient adaptive cascade lattice structure

A new cascaded lattice realization of nonlinear and linear phase finite impulse response filters based on an orthogonal polynomial approach is presented. An efficient least-mean-square-based adaptive algorithm is proposed to update the reflection coefficients, which minimizes the cost function with respect to the argument of a trigonometric function rather than the reflection coefficient itself. Results obtained based on simulations indicate significant improvements in convergence rate compared to the tapped delay line based LMS algorithm.

A simplified computational algorithm for implementing FIR digital filters

An N-point finite impulse response (FIR) digital filter, when implemented in software, generally requires N multiplications, N additions, and (N - 1) shifts per output sample. An obvious simplification is to implement the shift register required to store x(n) to x(n - N + 1) using a moving pointer, thereby eliminating the (N - 1) shifts per sample required in the most straightforward implementation. However, this simplification requires a check on the index of every sample to see if the end of the linear storage array has been passed, thereby voiding most of the gain in speed which was obtained. A simple technique is discussed for trading N storage locations for the (N - 1) shifts (or the (N - 1) index checks), thereby leading to an implementation in which only N multiplications, N additions, and one indexing operation are required per output sample. For implementing symmetric (i.e., linear phase) FIR filters, the resulting savings is even somewhat greater because two index pointers are required, and each must normally be checked to see that it remains within the bounds of the array.

Variable cutoff linear phase digital filters

This paper discusses an approach to the Implementation of a linear phase finite impulse response filter for which the cutoff frequency is controlled through a small number of parameters. The approach is based on a transformation implemented by replacing a subnetwork in a prototype network.