A new recursive algorithm for multiuser detection

Based on the synthesis and analysis of recursive receivers,a new algorithm,namely partial grouping maximization likelihood algorithm,is proposed to achieve satisfactory performance with moderate computational complexity.During the analysis,some interesting properties shared by the proposed procedures are described.Finally,the performance assessment shows that the new scheme is superior to the linear detector and ordinary grouping algorithm,and achieves a bit-error rate close to that of the optimum receiver.     

A recursive variance-reduction algorithm for estimatingcommunication-network reliability

In evaluating the capacity of a communication network architecture to resist possible faults of some of its components, several reliability metrics are used. This paper considers the 𝒦-terminal unreliability measure. The exact evaluation of this parameter is, in general, very costly since it is in the NP-hard family. An alternative to exact evaluation is to estimate it using Monte Carlo simulation. For highly reliable networks, the crude Monte Carlo technique is prohibitively expensive; thus variance reduction techniques must be used. We propose a recursive variance-reduction Monte-Carlo scheme (RVR-MC) specifically designed for this problem, RVR-MC is recursive, changing the original problem into the unreliability evaluation problem for smaller networks. When all resulting systems are either up or down independently of components state, the process terminates. Simulation results are given for a well-known test topology. The speedups obtained by RVR-MC with respect to crude Monte Carlo are calculated for various values of component unreliability. These results are compared to previously published results for five other methods (bounds, sequential construction, dagger sampling, failure sets, and merge process) showing the value of RVR-MC     

A sequential regression algorithm for recursive filters

A sequential regression (s.e.r.) algorithm is derived for recursive or infinite impulse response (i.i.r.) adaptive filters. Results pertaining to using the algorithm in a system-identification experiment are also included.     

A recursive algorithm for the error probability evaluation of M-QAM

A general recursive algorithm for the efficient and accurate computation of the bit error rate (BER) of square-shaped M-QAM constellations over additive white Gaussian noise (AWGN) channels is derived. We take advantage of the relationship amongst different square-shaped M-QAM constellations using Gray coded bit mapping     

Standardized shrinking LORETA-FOCUSS (SSLOFO): a new algorithm for spatio-temporal EEG source reconstruction

This paper presents a new algorithm called Standardized Shrinking LORETA-FOCUSS (SSLOFO) for solving the electroencephalogram (EEG) inverse problem. Multiple techniques are combined in a single procedure to robustly reconstruct the underlying source distribution with high spatial resolution. This algorithm uses a recursive process which takes the smooth estimate of sLORETA as initialization and then employs the re-weighted minimum norm introduced by FOCUSS. An important technique called standardization is involved in the recursive process to enhance the localization ability. The algorithm is further improved by automatically adjusting the source space according to the estimate of the previous step, and by the inclusion of temporal information. Simulation studies are carried out on both spherical and realistic head models. The algorithm achieves very good localization ability on noise-free data. It is capable of recovering complex source configurations with arbitrary shapes and can produce high quality images of extended source distributions. We also characterized the performance with noisy data in a realistic head model. An important feature of this algorithm is that the temporal waveforms are clearly reconstructed, even for closely spaced sources. This provides a convenient way to estimate neural dynamics directly from the cortical sources.     

A recursive link adaptation algorithm for MIMO systems

An algorithm to adjust the coding/modulation (CM) scheme in a multiple-input multiple-output (MIMO) wireless communication system is proposed and analysed. The CM scheme selected for each transmitter is determined by a recursive procedure at the receiver, taking into account estimated signal-to-noise ratio and the properties of available CM schemes. The algorithm performance was tested with different detection algorithms: pseudo-inverse (PINV), V-BLAST and maximum likelihood (ML).     

A robust recursive least squares algorithm

A new algorithm is developed, which guarantees the normalized bias in the weight vector due to persistent and bounded data perturbations to be bounded. Robustness analysis for this algorithm has been presented. An approximate recursive implementation is also proposed. It is termed as the robust recursive least squares (RRLS) algorithm since it resembles the RLS algorithm in its structure and is robust with respect to persistent bounded data perturbation. Simulation results are presented to illustrate the efficacy of the RRLS algorithm     

A generalized recursive algorithm for wave-scattering solutions intwo dimensions

A generalized recursive algorithm valid for both the E _z and H_z wave scattering of densely packed scatterers in two dimensions is derived. This is unlike previously derived recursive algorithms which have been found to be valid only for E_z polarized waves. In this generalized recursive algorithm, a scatterer is first divided into N subscatterers. The n-subscatterer solution is then used to solve the (n+n')-subscatterer solution. The computational complexity of such an algorithm is found to be of O (N²) in two dimensions while providing a solution valid for all angles of incidence. This is better than the method of moments with Gaussian elimination, which has an O(N³) complexity     

A recursive maximum likelihood algorithm for ARMA spectral estimation

A spectral estimation technique is presented for autoregressive moving-average (ARMA) processes. The technique is based on a parameter estimation technique known as the rec ursive maximum likelihood (RML) method. The recursive spectral estimation algorithm is presented and its asymptotic properties are discussed. Simulation results are presented to illustrate the performance of the estimator for various types of data.     

A recursive algorithm for computing Cramer-Rao-type bounds onestimator covariance

We give a recursive algorithm to calculate submatrices of the Cramer-Rao (CR) matrix bound on the covariance of any unbiased estimator of a vector parameter &thetas;_. Our algorithm computes a sequence of lower bounds that converges monotonically to the CR bound with exponential speed of convergence. The recursive algorithm uses an invertible “splitting matrix” to successively approximate the inverse Fisher information matrix. We present a statistical approach to selecting the splitting matrix based on a “complete-data-incomplete-data” formulation similar to that of the well-known EM parameter estimation algorithm. As a concrete illustration we consider image reconstruction from projections for emission computed tomography     

A gradient algorithm for center-frequency adaptive recursive bandpass filters

Mean-square output of a center-frequency variable bandpass filter is employed as the performance criterion to make the filter self-adjusting to the center frequency of the input signal. A gradient ascending algorithm is proposed to update the center-frequency-dependent coefficients of the filter to maximize the performance function.     

A recursive linear detection algorithm for asynchronous CDMAcommunication system

A recursive linear detection algorithm is proposed for the detection of signals from an asynchronous direct-sequence code-division multiple-access (DS-CDMA) communication system. This algorithm works for short as well as long codes. Under some reasonable conditions, this algorithm is proved to be stable and converges to the ideal decorrelating detector (IDD) with a sufficiently large memory length. The performance of the algorithm is analyzed in some detail. Upper and lower bounds for the bit-error probabilities are developed. It is demonstrated that the two bounds converge to the bit-error probabilities of the IDD as the large memory length increases. Simulation results show that the recursive detector proposed outperforms the truncated decorrelating detector with less memory and less computational complexity     

A new recursive algorithm for the reliability evaluation of a distributed program

The reliability of a distributed program is very sensitive to the ways of file distribution, and communication system topology. It is usually much more complex to analyze the reliability of distributed program than that of the network reliability. This paper presents a distributed program reliability analysis algorithm that is developed based on the concept of sharp operation. The algorithm provides a (E−n+2) * E memory space requirement and O(n+E+E*N_t) computation time, where E is the number of edges, n is the number of nodes, and N_t is the number of file spanning trees in the corresponding graph of distributed system, respectively. Compared with existing algorithms, the proposed algorithm is considered more economic both in time and space.     

A 2-D recursive inverse adaptive algorithm

In this paper, a 2-D form of the recently proposed recursive inverse (RI) adaptive algorithm is introduced. The filter coefficients can be updated along both the horizontal and vertical directions on a 2-D plane. The proposed approach uses a variable step size and avoids the use of the inverse autocorrelation matrix in the coefficient update equation, which leads to an improved and more stable performance. Performance of the 2-D RI algorithm is compared to that of the 2-D RLS algorithm in an image deconvolution and an adaptive line enhancer problem settings. The simulation results show that the proposed 2-D RI algorithm leads to an improved performance compared to that of the 2-D RLS algorithm.     

A unified fast recursive algorithm for data shuffling in variousorders

Data shuffling in a particular order is frequently required in signal processing applications. The authors present fast recursive algorithms, of order O(N), for shuffling a data sequence in various orders, e.g. bit reversed, Gray code, and other related orders, under a unified framework. These algorithms are computationally efficient in that every permutation index is essentially computed by a single logical or arithmetic operation between a previous index and a proper offset. The proposed algorithms can be used for the fast Fourier transform, fast Hartley transform, and mutual conversion among three typical forms of the Walsh transform     

A recursive and parallel fast JPDA algorithm

Joint Probabilistic Data Association (JPDA) is a very fine optimal multitarget tracking and association algorithm in clutter. However, the calculation explosion effect in computation of association probabilities has been a difficulty. This paper will discuss a method based on layered searching construction of association hypothesis events. According to the method, the searching schedule of the association events between two layers can be recursive and with independence, so it can also be implemented in parallel structure. Comparative analysis of the method with relative methods in other references and corresponding computer simulation tests and results are also given in the paper.     

二维滑动矩形窗傅氏变换的快速递推算法

该文利用相邻滑动窗数据之间的关系以及傅氏变换的平移性质,提出一种二维滑动矩形窗傅氏变换的快速递推算法。文中分析了该快速递推算法的复杂度和传统直接计算法的复杂度,证明了新的快速递推法可以大大降低计算复杂性,尤其是在图像尺寸和窗口尺寸较大的场合中。该算法可以改善滑窗傅氏变换或Gabor变换的计算效率。     

One-multiplier adaptive lattice algorithm for recursive filters

The formulation of one-multiplier lattice structures of the Gray-Markel type forinfinite impulse response filters is reviewed. Several special cases of this formulation — including the well-known Gray-Markel normalized lattice—are presented as scaled polynomial versions of the two-multiplier lattice. A new adaptive algorithm is presented for updating the parameters of one-multiplier lattice structured recursive filters. The LMS-based algorithm requires fewer computations than earlier reported algorithms [1]–[4].The research reported here was conducted with funds administered by the Naval Postgraduate School research council.     

A recursive algorithm for maximum likelihood-based identificationof blur from multiple observations

A maximum likelihood-based method is proposed for blur identification from multiple observations of a scene. When the relations among the blurring functions are known, the estimate of blur obtained using the proposed method is very good. Since direct computation of the likelihood function becomes difficult as the number of images increases, we propose an algorithm to compute the likelihood function recursively.     

The recursive pyramid algorithm for the discrete wavelet transform

The recursive pyramid algorithm (RPA) is a reformulation of the classical pyramid algorithm (PA) for computing the discrete wavelet transform (DWT). The RPA computes the N-point DWT in real time (running DWT) using just L(log N-1) words of storage, as compared with O(N) words required by the PA. L is the length of the wavelet filter. The RPA is combined with the short-length FIR filter algorithms to reduce the number of multiplications and additions