滤波器组的多滤波器联合能量频谱感知算法

针对认知无线电系统,设计了一种基于滤波器组的多滤波器联合能量频谱感知算法.分析了算法的基本原理,给出了算法的流程,并以信噪比为参数说明了算法的优越性.仿真验证算法的检测概率与漏失概率,并对经典滤波器组的能量频谱感知算法的检测概率与漏失概率进行了比较,结果表明:本算法性能优于经典滤波器组能量频谱感知算法的性能.     

ECG beat detection using filter banks

The authors have designed a multirate digital signal processing algorithm to detect heartbeats in the electrocardiogram (ECG). The algorithm incorporates a filter bank (FB) which decomposes the ECG into subbands with uniform frequency bandwidths. The FB-based algorithm enables independent time and frequency analysis to be performed on a signal. Features computed from a set of the subbands and a heuristic detection strategy are used to fuse decisions from multiple one-channel beat detection algorithms. The overall beat detection algorithm has a sensitivity of 99.59% and a positive predictivity of 99.56% against the MIT/BIH database. Furthermore this is a real-time algorithm since its beat detection latency is minimal. The FB-based beat detection algorithm also inherently lends itself to a computationally efficient structure since the detection logic operates at the subband rate. The FB-based structure is potentially useful for performing multiple ECG processing tasks using one set of preprocessing filters     

Optimization of filter banks using cyclostationary spectralanalysis

This paper proposes a design method of optimal biorthogonal FIR filter banks that minimize the time-averaged mean squared error (TAMSE) when the high-frequency subband signal is dropped. To study filter banks from a statistical point of view, cyclostationary spectral analysis is used since the output of the filter bank for a wide-sense stationary input is cyclostationary. First, the cyclic spectral density of the output signal is derived, and an expression for the TAMSE is presented. Then, optimal filter banks are given by minimizing the TAMSE with respect to the coefficients of the filters under the biorthogonality condition. By imposing the additional constraints on the coefficients, the optimal biorthogonal linear phase filter bank can be obtained     

Partial spectrum reconstruction using digital filter banks

The problem of reconstructing a part of the spectrum is reduced to designing the filter bank to satisfy a set of conditions. For the case considered here, these conditions cannot be satisfied simultaneously, so perfect reconstruction is not possible. The necessary and sufficient conditions on the filters so that the resulting filter bank cancels most alias components are found. Such filter banks are called partial alias cancellation filter banks. The product of the polyphase transfer matrices of these filter banks must be a block pseudocirculant matrix. An algorithm design procedure is discussed, and examples are given to demonstrate the theory     

Oversampled filter banks from extended perfect reconstruction filter banks

Oversampled filter banks are currently being proposed for robust transmission applications. In this paper, we completely characterize multidimensional doubly finite-impulse-response (FIR) filter banks, that is, oversampled filter banks whose dual is FIR. Then, we consider the problem of extending perfect reconstruction critically sampled multidimensional filter banks in order to obtain doubly FIR (DFIR) filter banks. As a result, very simple criteria for constructing DFIR filter banks as extensions of orthogonal filter banks are obtained. This paper also analyzes the problem of constructing totally FIR filter banks, i.e., DFIR filter banks that remain DFIR even when some channels are removed. It is shown that any totally FIR filter bank can be implemented as the cascade of a critically sampled DFIR filter bank whose number of channels is equal to the subsampling factor, a redundant finite-dimensional transform, and a suitable set of delays.     

Subband coding of images using asymmetrical filter banks

We address the problem of the choice of subband filters in the context of image coding. The ringing effects that occur in subband-based compression schemes are the major unpleasant distortions. A new set of two-band filter banks suitable for image coding applications is presented. The basic properties of these filters are linear phase, perfect reconstruction, asymmetric length, and maximum regularity. The better overall performances compared to the classical QMF subband filters are explained. The asymmetry of the filter lengths results in a better compaction of the energy, especially in the highpass subbands. Moreover, the quantization error is reduced due to the short lowpass synthesis filter. The undesirable ringing effect is considerably reduced due to the good step response of the synthesis lowpass filter. The proposed design takes into account the statistics of natural images and the effect of quantization errors in the reconstructed images, which explains the better coding performance.     

Noise reduction in oversampled filter banks using predictivequantization

We introduce two methods for quantization noise reduction in oversampled filter banks. These methods are based on predictive quantization (noise shaping or linear prediction). It is demonstrated that oversampled noise shaping or linear predictive subband coders are well suited for subband coding applications where, for technological or other reasons, low-resolution quantizers have to be used. In this case, oversampling combined with noise shaping or linear prediction improves the effective resolution of the subband coder at the expense of increased rate. Simulation results are provided to assess the achievable quantization noise reduction and resolution enhancement, and to investigate the rate-distortion properties of the proposed methods     

Cognitive wideband spectrum sensing using cosine-modulated filter banks

A multichannel joint spectrum sensing strategy based on cosine-modulated filter banks (CMFBs) was developed to improve sensing efficiency. The received wideband signal was split into several bands through the filters that are constructed by grouping continuous sub-band filters. Through flexibly designing prototype filter, not only the spectrum of non-uniform bandwidth can be estimated, but also the spectral leakage between adjacent channels can be adjusted. The probabilities of false alarm and detection for multichannel jointly spectrum sensing in the Rayleigh fading channel were deduced. The decision thresholds of different channels were obtained as regards the probability of false alarm. Simulation results show that compared with the traditional energy detector, the detection capability and sensing efficiency have been improved, especially at low signal-to-noise ratio. The CMFB-based multichannel joint sensing scheme not only increases the efficiency of detection, but also enhances the flexibility on the control of bandwidth and spectral leakage between neighbouring channels.     

Efficient interpolators and filter banks using multiplier blocks

We examine the use of efficient shift-and-add multiplier structures and multiplier blocks to reduce computational complexity in filter banks. This is more efficient than treating each bank filter separately. We also examine the Farrow (see Proc. Int. Symp. Circuits Syst. (ISCAS), p. 2641-2645) structure, which is used in interpolators. Applying multiplier blocks makes this structure cheaper than the more recognized Lagrange interpolator     

Equalization issues in multicarrier transmission using filter banks

In multicarrier data transmission using filter banks, adaptive equalizers can be introduced in the receiver in every subchannel, to achieve high bit rates. Following conventional data transmission techniques, two approaches can be envisaged, namely the double sampling equalizer and the critical sampling equalizer. Both schemes are discussed and assessed in the present paper, in the multicarrier context. Estimations are given for the lengths of the equalizers as a function of the channel distortion and of the roll-off factor of the prototype filter in the receiver filter bank. The importance of the roll-off factor is stressed, since it controls the computational complexity of the system. Simulation results associated with two channel models are given to support the theoretical analysis. They show that the critical sampling approach has an advantage in computation rate over the double sampling scheme, when the prototype filter roll-off is above 0.5 and when the mean square output error is the performance criterion and no timing offset is introduced.     

利用参考波形估计导航信号测距偏差

针对卫星导航信号存在的微小信号畸变,研究了因导航信号畸变而引起的测距偏差的估计问题。基于理想矩形脉冲波形和真实信号波形的上升沿零交叉点信息,给出参考波形定义,并以此为基础估计测距偏差。该方法可用于定量评估卫星导航信号波形畸变对测距偏差的影响及比较卫星之间的测距差异。以二阶模型为基础产生畸变波形,验证了该方法的有效性,并分析了估计精度与信噪比关系。通过大口径天线采集“北斗”卫星B1频点信号,利用该方法获得了B1频点I/Q支路信号的测距偏差,表明该方法可用于在轨卫星信号的测距性能评估。     

Estimation of fractal signals using wavelets and filter banks

A filter bank design based on orthonormal wavelets and equipped with a multiscale Wiener filter was recently proposed for signal restoration and for signal smoothing of 1/f family of fractal signals corrupted by external noise. The conclusions obtained in these papers are based on the following simplificative hypotheses: (1) The wavelet transformation is a whitening filter, and (2) the approximation term of the wavelet expansion can be avoided when the number of octaves in the multiresolution analysis is large enough. In this paper, we show that the estimation of 1/f processes in noise can be improved avoiding these two hypotheses. Explicit expressions of the mean-square error are given, and numerical comparisons with previous results are shown     

Nonparametric Bayes-risk estimation

Two nonparametric methods to estimate the Bayes risk using classified sample sets are described and compared. The first method uses the nearest neighbor error rate as an estimate to bound the Bayes risk. The second method estimates the Bayes decision regions by applying Parzen probability-density function estimates and counts errors made using these regions. This estimate is shown to be asymptotically consistent in mean square. The results of experiments with these estimators on simulated and empirical data imply that the estimators both have acceptable small-sample properties; however, small-sample convergence of both estimators depends strongly on the choice of metric and local area or window size in the measurement space.     

Order statistic filter banks

Filter banks play a major role in multirate signal processing where these have been successfully used in a variety of applications. In the past, filter banks have been developed within the framework of linear filters. It is well known, however, that linear filters may have less than satisfactory performance whenever the underlying processes are non-Gaussian. We introduce the nonlinear class of order statistic (OS) filter banks that exploit the spectral characteristics of the input signal as well as its rank-ordering structure. The attained subband signals provide frequency and rank information in a localized time interval. OS filter banks can lead to significant gains over linear filter banks, particularly when the input signals contain abrupt changes and details, as is common with image and video signals. OS filter banks are formed using traditional linear filter banks as fundamental building blocks. It is shown that OS filter banks subsume linear filter banks and that the latter are obtained by simple linear transformations of the former. To illustrate the properties of OS filter banks, we develop simulations showing that the learning characteristics of the LMS algorithm, which are used to optimize the weight taps of OS filters, can be significantly improved by performing the adaptation in the OS subband domain.     

THEORY AND DESIGN OF UNIFORM FILTER BANKS USING ALL-PASS FILTERS

In this paper,the theory of uniform filter banks using all-pass tilters is furtherdeveloped.A new structure of two stage filter banks using all-pass filter is proposed,The pre-stage is half-band filter with period,the post-stage is two sets of band-pass filter banks.Thepre-stage filter stop-band just controls the don't-care-band of the post-stage filter banks usingall-pass polyphase,so as to realize a continuous stop-band property Moreover,a method ofsynthesizing filter bank is derived,which eliminates aliasing and amplitude distortions of theanalysis/synthesis system Finally,an example is given.     

Design of IIR orthogonal wavelet filter banks using lifting scheme

The lifting scheme is well known to be an efficient tool for constructing second generation wavelets and is often used to design a class of biorthogonal wavelet filter banks. For its efficiency, the lifting implementation has been adopted in the international standard JPEG2000. It is known that the orthogonality of wavelets is an important property for many applications. This paper presents how to implement a class of infinite-impulse-response (IIR) orthogonal wavelet filter banks by using the lifting scheme with two lifting steps. It is shown that a class of IIR orthogonal wavelet filter banks can be realized by using allpass filters in the lifting steps. Then, the design of the proposed IIR orthogonal wavelet filter banks is discussed. The designed IIR orthogonal wavelet filter banks have approximately linear phase responses. Finally, the proposed IIR orthogonal wavelet filter banks are applied to the image compression, and then the coding performance of the proposed IIR filter banks is evaluated and compared with the conventional wavelet transforms.     

Design of filter banks using transformation of variables: newresults

The design problem of multirate filter banks can be divided into two parts. The first part involves the issue of reconstruction errors. The second part involves the issue of designing good quality subband filters. There is a class of techniques that we refer to as transformation of variables which satisfactorily addresses the two parts of the design problem. This class of filter banks is specified by its prototype filters and transformation (kernel). It is the flexibility and relative ease in designing the kernel that enables the technique to satisfactorily address the second part of the design problem. We present two new methods of designing the kernel that will enhance the design techniques' flexibility and effectiveness. The first is the combination of the McClellan transformation and rotation operators. The second introduces and uses the concept of directional singular value decomposition (SVD)     

A novel center of mass method for estimation of center frequency and spectral edges in CR using filter banks

In this paper, we propose a novel multistage DFT based polyphase filter bank technique using center of mass approach for estimating center frequency, detecting spectral edges and identifying spectral holes in wideband cognitive radio (CR) for efficient utilization of radio frequency spectrum. Spectral holes are identified by measuring energy at the output of individual subband of filter banks. Accuracy of spectral holes detection depends on frequency resolution of subbands and can be increased with an increase in number of DFT points, however, at the expense of computational complexity. In order to reduce complexity our algorithm starts with a coarser spectral resolution in the first stage. If a primary user appears over more than one subband, center frequency can be estimated in the first stage using proposed approach. However, if the primary user appears exclusively within a single subband, center frequency can be estimated at the second stage. For center frequency estimation, we propose a novel center of mass approach to achieve better precision, where mass is related to energy and distance is related to frequency. Exhaustive simulation results show that center frequency estimation using proposed multistage polyphase filter bank based on center of mass reduces computational complexity and has higher precision compared to conventional filter bank methods.     

Effects of model errors on waveform estimation using the MUSICalgorithm

Sensor arrays are frequently used to separate and reconstruct superimposed signals arriving from different directions. The paper studies the effect of model errors, i.e., differences between the assumed and actual array response, on the quality of the reconstructed signals. Model errors are the limiting factor of array performance when the observation time is sufficiently long. The authors analyze a signal estimation technique which is based on the MUSIC algorithm. Formulas are derived for the signal-to-interference and signal-to-noise ratios as function of the model errors. By evaluating these formulas for selected test cases they gain some insights into the sensitivity of the signal estimation problem to model uncertainty     

余弦调制滤波器组的原型滤波器设计

该文提出了一种近似重构的余弦调制滤波器组的原型滤波器设计方法。该方法将原型滤波器表示成A(z2)B(z)的形式(其中B(z)是最平坦FIR滤波器),通过优化低阶FIR滤波器A(z)的通带边缘频率,间接设计原型滤波器。文中给出的设计例子表明,该方法可获得很高阻带衰减的滤波器组。