利用非标准的扬声器布置重发双通路立体声

提出一种利用非标准的扬声器布置重发双通路立体声的方法。理论和实验结果表明，通过虚拟声信号处理的方法，可在一定程度上改善扬声器的非标准布置所引起的声像位置畸变。     

Adaptive mixed-rank filters

Proposes an adaptive median-type filtering scheme which is both computationally efficient and effective in suppressing impulsive noise from images without loss of image detail. A fast implementation is briefly discussed and comparisons with other filters are presented.<>     

Adaptive polynomial filters

Adaptive nonlinear filters equipped with polynomial models of nonlinearity are explained. The polynomial systems considered are those nonlinear systems whose output signals can be related to the input signals through a truncated Volterra series expansion or a recursive nonlinear difference equation. The Volterra series expansion can model a large class of nonlinear systems and is attractive in adaptive filtering applications because the expansion is a linear combination of nonlinear functions of the input signal. The basic ideas behind the development of gradient and recursive least-squares adaptive Volterra filters are first discussed. Adaptive algorithms using system models involving recursive nonlinear difference equations are then treated. Such systems may be able to approximate many nonlinear systems with great parsimony in the use of coefficients. Also discussed are current research trends and new results and problem areas associated with these nonlinear filters. A lattice structure for polynomial models is described     

Adaptive Laguerre-lattice filters

Adaptive Laguerre-based filters provide an attractive alternative to adaptive FIR filters in the sense that they require fewer parameters to model a linear time-invariant system with a long impulse response. We present an adaptive Laguerre-lattice structure that combines the desirable features of the Laguerre structure (i.e., guaranteed stability, unique global minimum, and small number of parameters M for a prescribed level of modeling error) with the numerical robustness and low computational complexity of adaptive FIR lattice structures. The proposed configuration is based on an extension to the IIR case of the FIR lattice filter; it is a cascade of identical sections but with a single-pole all-pass filter replacing the delay element used in the conventional (FIR) lattice filter. We utilize this structure to obtain computationally efficient adaptive algorithms (O(M) computations per time instant). Our adaptive Laguerre-lattice filter is an extension of the gradient adaptive lattice (GAL) technique, and it demonstrates the same desirable properties, namely, (1) excellent steady-state behavior, (2) relatively fast initial convergence (comparable with that of an RLS algorithm for Laguerre structure), and good numerical stability. Simulation results indicate that for systems with poles close to the unit circle, where an (adaptive) FIR model of very high order would be required to meet a prescribed modeling error, an adaptive Laguerre-lattice model of relatively low order achieves the prescribed bound after just a few updates of the recursions in the adaptive algorithm     

Adaptive lattice filters for CDMA overlay

This paper presents the behavior of reflection coefficients of a stochastic gradient lattice (SGL) filter applied to a code division multiple-access overlay system. Analytic expressions for coefficients for a two-stage filter are derived in a Rayleigh fading channel with the presence of narrow-band interference and additive white Gaussian noise. It is shown that the coefficients of the lattice filter exhibit separate tracking and convergent properties, and that compared to an LMS filter, the lattice filter provides fast rate of convergence, while having good capability of narrow-hand interference suppression     

现代声重放系统的发展史

从20世纪50年代开始的多声道声音的商业应用开始,介绍了电影院"立体声"(stereo)、环绕声概念。接着介绍了1958年出现的两声道立体声及最终四声道装置的成败。提到了从20世纪70年代起出现的Dolby stereo及80年代中期电影院环绕声声道—代中期电影院surround技术。还简单介绍了1992年出现的杜比数字技术:Dolby Digital,Dolby Digital EX和Dolby E的特点及与电影院、家庭影院的关系。最后,简述了虚拟环绕声的实现与优缺点。文章还叙述了今后声系统发展要解决的多个关键问题。本文根据俄罗斯网上电子版教学参考书АКУСТИЧЕСКИЕСИСТЕМЫ2016版第四章内容译出。     

Adaptive multichannel filters for colour image processing

This paper addresses the problem of noise suppression for multichannel data, such as colour images. The proposed filters utilize adaptive data dependent nonparametric techniques. Simulation results indicate that the new filters suppress impulsive as well as Gaussian noise and preserve edges and details.     

Adaptive lattice bilinear filters

Two fast least-squares lattice algorithms for adaptive nonlinear filters equipped with bilinear system models are presented. The lattice filter formulation transforms the nonlinear filtering problem into an equivalent multichannel linear filtering problem, thus using multichannel lattice filtering algorithms to solve the nonlinear filtering problem. The computational complexity of the algorithms is an order of magnitude smaller than that of previously available methods. The first of the two approaches is an equation error algorithm that uses the measured desired response signal directly to compute the adaptive filter outputs. This method is conceptually very simple, but results in biased system models in the presence of measurement noise. The second is an approximate least-squares output error solution; the past samples of the output of the adaptive system itself are used to produce the filter output at the current time. Results indicate that the output error algorithm is less sensitive to output measurement noise than the equation error method     

Adaptive filters suitable for real-time spectral analysis

New cascade structures for adaptive filters are presented. They are especially suitable for real-time applications. Since the new structures are intended to be realized using single-chip DSP ICs or single-chip custom VLSI circuits, the requirements for memory and divisions are minimized. The new structures are based on state-variable biquads that in addition to having good SNRs and low sensitivities (for fixed-point implementations) can also have their resonant frequencies and Q-factors independently tuned. The special cases of using the adaptive filters for tracking sinusoids corrupted by noise and for formant based speech compression are described in detail.     

Adaptive invariant novelty filters

The multiple-channel novelty filters of associative memory are derived from the retina neuron network point-spread function. Scale and rotation invariance is achieved by the input data flowing through the nonuniform polar exponential sampling to a uniform output space. Image domain bandpassing techniques are then used to extract the low-band and high-band frequency contents of the equivalent novelty filters.     

Adaptive LMS filters for cellular CDMA overlay situations

This paper extends and complements previous research we have performed on the performance of nonadaptive narrowband suppression filters when used in cellular code-division multiple-access (CDMA) overlay situations. An adaptive least mean square (LMS) filter is applied to a cellular CDMA overlay in order to reject narrowband interference. An accurate expression for the steady-state tap-weight covariance matrix is derived for the real LMS algorithm for arbitrary statistics of the overlaid interference. Numerical results illustrate that when the ratio of the narrowband interference bandwidth to the spread spectrum bandwidth is small, the LMS filter is very effective in rejecting the narrowband interference. Furthermore, it is seen that the performance of the LMS filter in a CDMA overlay environment is not significantly worse than the performance of an ideal Wiener filter, assuming the LMS filter has had sufficient time to converge     

Optimal approximate inverse of linear periodic filters

We propose a method for constructing optimal causal approximate inverse for discrete-time single-input single-output (SISO) causal periodic filters in the presence of measurement noise. The analysis is based on block signals and multi-input multi-output (MIMO) time-invariant models for periodic filters. The objective function to be minimized is the asymptotic block mean square error. The optimization problem is formulated in terms of transfer matrices as an optimal model-matching problem with nonsquare model and plant. Based on an inner-outer factorization on the transpose of the plant rational matrix, it is shown that the problem can be further reduced to one with a lower dimensional square model and plant, which is then solved in the time-domain, and a closed-form solution is obtained. A lower bound on the objective function is given. It is shown that the lower bound can be asymptotically achieved as the order of the optimal transfer matrix increases. The proposed method is extended to MIMO periodic systems. Numerical examples are used to illustrate the performance of the proposed approximate inverse.     

Adaptive parallel-cascade truncated Volterra filters

This paper studies adaptive truncated Volterra filters employing parallel-cascade structures. Parallel-cascade realizations implement higher order Volterra systems as a parallel connection of multiplicative combinations of lower order truncated Volterra systems. A normalized LMS adaptive filter is developed, and its performance capabilities are evaluated using a series of simulation experiments. The experimental results indicate that the normalized LMS adaptive parallel-cascade Volterra filter has superior convergence properties over several competing structures. This paper also includes an experiment that demonstrates the capability of the parallel-cascade adaptive system to reduce its implementation complexity by using fewer than the maximum number of branches required for the most general realization of the system     

Alternating fixed-point algorithm for stereophonic acoustic echocancellation

A novel algorithm for use in stereophonic acoustic echo cancellation is introduced. The alternating fixed-point structure of the algorithm descends each of the channels alternatively and avoids nonuniqueness in the solutions by employing inter- and intra-channel orthogonal projections. For a noisy environment, the algorithm is shown to provide improved misalignment performance and echo cancellation over leading competitors at a low computational cost. The inherent noise robustness is uncovered using H^∞ estimation techniques and noise-error bounds are derived     

Transmitter-based inverse filters for reducing MAI and ISI in CDMA-TDD downlink

Inverse filters (INVF) are introduced as a new transmitter-based precoding scheme for the code-division multiple access-time division duplex (TDD) downlink. Multiple access interference and intersymbol interference are significantly reduced while the mobile station's structure is reduced to a filter matched to the user's spreading code. The method assumes knowledge of the channel at the transmitter which is feasible under TDD. The new algorithm uses a minimum mean-squared error criterion with power constraint. When compared with existing schemes, INVF increase the system performance while maintaining a low computational cost. The theoretical analysis is supported with simulation results. Analytical bit-error rates for any precoding algorithm is also calculated.     

Adaptive Volterra filters for active control of nonlinear noiseprocesses

This paper presents a Volterra filtered-X least mean square (LMS) algorithm for feedforward active noise control. The research has demonstrated that linear active noise control (ANC) systems can be successfully applied to reduce the broadband noise and narrowband noise, specifically, such linear ANC systems are very efficient in reduction of low-frequency noise. However, in some situations, the noise that comes from a dynamic system may he a nonlinear and deterministic noise process rather than a stochastic, white, or tonal noise process, and the primary noise at the canceling point may exhibit nonlinear distortion. Furthermore, the secondary path estimate in the ANC system, which denotes the transfer function between the secondary source (secondary speaker) and the error microphone, may have nonminimum phase, and hence, the causality constraint is violated. If such situations exist, the linear ANC system will suffer performance degradation. An implementation of a Volterra filtered-X LMS (VFXLMS) algorithm based on a multichannel structure is described for feedforward active noise control. Numerical simulation results show that the developed algorithm achieves performance improvement over the standard filtered-X LMS algorithm for the following two situations: (1) the reference noise is a nonlinear noise process, and at the same time, the secondary path estimate is of nonminimum phase; (2) the primary path exhibits the nonlinear behavior. In addition, the developed VFXLMS algorithm can also be employed as an alternative in the case where the standard filtered-X LMS algorithm does not perform well     

Exponential asymptotic stability of time-varying inverse predictionerror filters

It is a classical result of linear prediction theory that as long as the minimum prediction error variance is nonzero, the transfer function of the optimum linear prediction error filter for a stationary process is minimum phase, and therefore, its inverse is exponentially stable. Here, extensions of this result to the case of nonstationary processes are investigated. In that context, the filter becomes time-varying, and the concept of “transfer function” ceases to make sense. Nevertheless, we prove that under mild condition on the input process, the inverse system remains exponentially stable. We also consider filters obtained in a deterministic framework and show that if the time-varying coefficients of the predictor are computed by means of the recursive weighted least squares algorithm, then its inverse remains exponentially stable under a similar set of conditions     

Adaptive filters to improve loudspeaker telephone

A loudspeaking telephone is under development which uses two adaptive filters to cancel acoustic and electric coupling in an open-loop or shallow voice-switched system. Measurements indicate that between 15 and 30 dB of echo cancellation is available for a range of conditions.     

Adaptive speckle filters and scene heterogeneity

The presence of speckle in radar images makes the radiometric and textural aspects less efficient for class discrimination. Many adaptive filters have been developed for speckle reduction, the most well known of which are analyzed. It is shown that they are based on a test related to the local coefficient of variation of the observed image, which describes the scene heterogeneity. Some practical criteria are introduced to modify the filters in order to make them more efficient. The filters are tested on a simulated synthetic aperture radar (SAR) image and an SAR-580 image. As was expected, the new filters perform better, i.e. they average the homogeneous areas better and preserve texture information, edges, linear features, and point target responses better at the same time. Moreover, they can be adapted to features other than the coefficient of variation to reduce the speckle while preserving the corresponding information     

一种用于抑制直扩通信中窄带干扰的非线性自适应方法

在分析线性自适应滤波抑制单频干扰、自回归过程窄带干扰和窄带BPSK调制信号干扰的性能的基础上,提出了一种非线性自适应波抑制方法.在对窄带干扰进行预测前,通过对扩谱信号的估计,使得窄带干扰预测的背景噪声由非高斯转变为高斯,并消除扩谱信号对干扰估计的影响,再通过NLMS和RLS自适应算法进行干扰抑制.理论分析和仿真试验结果表明,这种改进方法对于系统性能的改善效果,明显优于常规自适应滤波抑制方法.