Design of arbitrary-phase variable digital filters using SVD-based vector-array decomposition

This paper proposes a straightforward method for designing variable digital filters with arbitrary variable magnitude as well as arbitrary fixed-phase or variable fractional delay (VFD) responses. The basic idea is to avoid the complicated direct design of one-dimensional (1-D) variable digital filters by decomposing the original variable filter design problem into easier subproblems that only require constant 1-D filter designs and multidimensional polynomial approximations. Through constant 1-D filter designs and multidimensional polynomial fits, we can easily obtain a variable digital filter satisfying the given variable design specifications. To decompose the original variable filter design into constant 1-D filter designs and multidimensional polynomial fits, a new multidimensional complex array decomposition called vector array decomposition (VAD) is proposed, which is based on two new theorems using the singular value decomposition (SVD). Once the VAD is obtained, the subproblems can be easily solved. Furthermore, we show that the VAD can also be generalized to the weighted least squares (WLS) case (WLS-VAD) for the WLS variable filter design. Three design examples are given to illustrate that the WLS-VAD and VAD-based techniques are considerably efficient for designing variable digital filters with arbitrary variable magnitude and arbitrary fixed-phase or VFD responses.     

Parallel algorithms for terminal-pair reliability

The parallelization of the two best-known sequential algorithms, that of W.P. Dotson and J.O. Gobein (1979) and that of L.B. Page and J.E. Perry (PP-F2TDN) (1989) for computing the terminal-pair reliability in a network is discussed. Reduce and Partition (R and P), a novel sequential algorithm which combines the best efficient features of these two algorithms, is presented. It is shown that R and P runs almost twice as fast as the previously known fastest algorithm. A parallel version of R and P is also presented. The execution times of all three parallel algorithms with various numbers of processors for different networks on the BBN Butterfly parallel computer are provided. The parallel algorithms were implemented on a shared-memory parallel computer. In R and P, the greedy approach was used in selecting shortest paths in order to locally minimize the number of subproblems. This selection did not consider the effect of reductions on the subproblems to be generated     

H-polarization diffraction by a thick metal-dielectricjoin

An analysis is presented of the H-polarization diffraction due to a material discontinuity formed by the junction of a thick dielectric half-plane with a metallic half-plane having the same thickness. This is accomplished by first considering the solution of several subproblems. These include the direct diffraction and coupling due to a plane wave incident on a loaded open-ended parallel plate waveguide and radiation and reflection by a waveguide mode. The final solution for diffraction by the metal-dielectric join is obtained by introducing a perfectly conducting stub within the loaded guide and subsequently using the generalized scattering matrix formulation with the stub brought to the waveguide opening. All the analysis relating to the subproblems is done by the dual integral equation approach. As expected, the final expressions involve several Wiener-Hopf split functions which are evaluated numerically or analytically     

Using generalized capacitated trees for designing the topology of local access networks

The design of the topology of a local access network is a complex process which builds on many different combinatorial optimization problems such as the concentrator quantity problem, the concentrator location problem, the terminal clustering problem and the terminal layout problem. Usually, these four subproblems are solved separably and sequentially and the solution of one subproblem is used as data for the next subproblem. There are two main drawbacks associated to this four‐phase approach: i) without knowing the optimal solution to the global problem it is difficult to set the parameters for some of the subproblems which appear in the earlier phases and ii) in many cases, wrong decisions taken at one of the earlier phases are “passed” to the subsequent phases. Our aim in this paper is to formulate the two last subproblems, clustering and layout, as one single generalized capacitated tree problem. We formulate the clustering/layout problem as a capacitated single‐commodity network flow problem with adequate capacities on the arcs. We adapt a reformulation presented in (Gouveia, 1995) of a single‐commodity flow model presented in (Gavish, 1983). We present several inequalities which can be used to tighten the LP relaxation of the original formulation. We present two heuristics for obtaining feasible solutions for the clustering/layout problem. Computational results taken from tests with 50, 100 and 200 nodes indicate that in most of the cases the best heuristic produces topologies with lower cost than the ones obtained by solving separately and sequentially the two individual subproblems. This revised version was published online in June 2006 with corrections to the Cover Date.     

Massively parallel classification of single-trial EEG signals using a min-max modular neural network

This paper presents a method for classifying single-trial electroencephalogram (EEG) signals using min-max modular neural networks implemented in a massively parallel way. The method has three main steps. First, a large-scale, complex EEG classification problem is simply divided into a reasonable number of two-class subproblems, as small as needed. Second, the two-class subproblems are simply learned by individual smaller network modules in parallel. Finally, all the individual trained network modules are integrated into a hierarchical, parallel, and modular classifier according to two module combination laws. To demonstrate the effectiveness of the method, we perform simulations on fifteen different four-class EEG classification tasks, each of which consists of 1491 training and 636 test data. These EEG classification tasks were created using a set of non-averaged, single-trial hippocampal EEG signals recorded from rats; the features of the EEG signals are extracted using wavelet transform techniques. The experimental results indicate that the proposed method has several attractive features. 1) The method is appreciably faster than the existing approach that is based on conventional multilayer perceptrons. 2) Complete learning of complex EEG classification problems can be easily realized, and better generalization performance can be achieved. 3) The method scales up to large-scale, complex EEG classification problems.     

超分辨测向中奇异值分解的FPGA实现

奇异值分解是超分辨测向技术的核心组成部分,现有的并行实现方案适用范围窄,运算量大,迭代时间长.为了满足测向接收机系统的高实时性需求,结合双边Jacobi算法的交换策略和单边Jacobi算法的求角结构,提出了一种改进的实现方法.该实现方法修正了脉动阵列的收敛性问题,提高了复数矩阵的收敛速度.同时,给出了算法的现场可编程门阵列(FPGA)实现结构.仿真结果证明该方案耗时在百微秒以内,能够应用于电子侦察设备.     

曲面共形阵列结构快速数值分析方法

针对曲面共形阵列结构电磁散射特性的高效、精确仿真分析需求,提出了一种并行综合函数矩量法处理方案.该方法是传统电磁经典数值算法——矩量法的一种改进形式,通过几何区域分解处理和综合基函数的方式极大降低了算法的内存消耗,使得单机分析电大尺寸问题和大规模阵列问题成为可能.更为重要的是,针对周期阵列结构,该方法具备综合函数复用特性和多区域并行处理特性,能够大大提高算法的综合处理效率.一个6×11的柱面共形贴片阵列被用于验证所提方法的性能,仿真结果表明,对于周期阵列结构,该方法的计算精度与多层快速多极子算法相当,虽然计算效率略低于多层快速多极子方法,但内存消耗比多层快速多极子方法低一个数量级.     

A generalized scattering matrix approach for analysis ofquasi-optical grids and de-embedding of device parameters

A generalized scattering matrix approach to analyzing quasi-optical grids used for grid amplifiers and grid oscillators is developed. The approach is verified by a novel method for de-embedding, in a waveguide simulator, the active device parameters of a differential pair high electron mobility transistor (HEMT) from the single unit cell of a grid amplifier. The method incorporates the additional ports presented to the active device into a method of moments solution of the embedding periodic array. The port(s) defined at the device or load location are within the plane of the array, and not terminated in a microstrip line with a known characteristic impedance. Therefore the generalized scattering matrix for the embedding array is normalized to the calculated input impedance(s) at these port(s). The approach described here uses a Floquet representation of the fields incident and reflected from the grid as the remaining ports in the generalized scattering matrix. The use of Floquet modes allows analysis of general geometries and nonnormal incident angles without the need for magnetic and electric wall assumptions. By developing a generalized scattering matrix for the embedding periodic array, this approach now allows conventional amplifier design techniques and analysis methods to be applied to quasi-optical grid amplifier and oscillator design. The major advantage of this unification for grid amplifier design being that the stability of the design can be predicted     

Maximum likelihood methods in radar array signal processing

We consider robust and computationally efficient maximum likelihood algorithms for estimating the parameters of a radar target whose signal is observed by an array of sensors in interference with unknown second-order statistics. Two data models are described: one that uses the target direction of arrival and signal amplitude as parameters and one that is a simpler, unstructured model that uses a generic target “spatial signature”. An extended invariance principle is invoked to show how the less accurate maximum likelihood estimates obtained from the simple model may be refined to achieve asymptotically the performance available using the structured model. The resulting algorithm requires two one-dimensional (1-D) searches rather than a two-dimensional search, as with previous approaches for the structured case. If a uniform linear array is used, only a single 1-D search is needed. A generalized likelihood ratio test for target detection is also derived under the unstructured model. The principal advantage of this approach is that it is computationally simple and robust to errors in the model (calibration) of the array response     

基于倍增FSR式光梳状滤波器阵列的瞬时频率测量研究

基于自由频谱区(FSR)倍数增长式光梳状滤波器阵列,设计了一种微波瞬时频率测量方案,实现了具有自然二进制编码的数字输出。待测微波信号经过载波抑制型单边带调制后加载到光波上产生一阶边带,而后将其输入到光梳状滤波器阵列中;阵列由多个梳状滤波器并联而成,它们滤波响应对应的FSR呈倍数增长趋势,最高位数字输出对应滤波器的FSR最大。滤波后输出的光信号经光电检测、比较和判决后,获得N位自然二进制码标识的频率值,提高了编码效率和测量精度。最后,在0～40GHz范围,验证了4位有效长度的数字编码式测频结果。     

Bit-level systolic algorithms for real symmetric and Hermitian eigenvalue problems

Arithmetic algorithms are presented that speed up the parallel Jacobi method for the eigen-decomposition of real symmetric and complex Hermitian matrices. The 2×2 submatrices to which the Jacobi rotations are applied form a Clifford algebra, hence they can be decomposed into a sum of even and odd part. This decomposition enables the application of the rotations from a single side instead of both, thus removing some sequentiality from the original Jacobi method. Moreover, with the help of implicit CORDIC algorithms, the rotations are evaluated and applied in a fully concurrent fashion on triangular arrays of specialized processors. The CORDIC algorithms employed in the complex case are genuine 3- and 4-dimensional generalizations of the 2-dimensional algorithm used in the real case. Because these algorithms are implicit, variants are obtained with minor modifications that perform rotations whose resolution is poor at first and slowly increases to become high in the last steps of the Jacobi method. Such variants further reduce the total computation time.     

Advances in multichannel MultiGbytes/s bit-parallel WDM singlefiber link

For ultra-high-speed single media parallel interconnects, an all optical single fiber WDM format of transmitting parallel bits rather than a fiber ribbon format-where parallel bits are sent through corresponding parallel fibers in a ribbon format, can be the media of choice. Here, we discuss the realization of a multi-km×Gb/s bit-parallel WDM (BP-WDM) single fiber link. The distance-speed product of this single fiber link is more than several orders of magnitude higher than that of a fiber ribbon link. The design of a 12 b parallel channels WDM system operating at 1 Gb/s per channel rate through a single fiber is first presented. Experimental results for a two channel system operating at that rate are given. Further improvement of distance-speed product for the BP-WDM link can be obtained with JPL's newly developed 20 Gb/s per channel laser diode array transmitter. Also, new computer simulation results on how a large amplitude co-propagating pulse may induce pulse compression on all the co-propagating data pulses, thereby improving the shaping of these pulses for a WDM system, are presented and discussed. The existence of WDM solitons is also shown     

采用基于CORDIC的脉动阵列实现MUSIC算法

针对MUSIC算法运算量大,实时性差的不足,对矩阵本征分解的Jacobi方法进行了并行改进,提出了在现场可编程门阵列上采用脉动阵列结构实现对数据协方差矩阵的高速并行分解,并对8×8矩阵进行了仿真,结果表明该算法运算速度快、实时性强,具有广泛的应用前景。     

广义Jacobi序列的自相关函数

相关函数是衡量序列密码安全性的重要指标。该文讨论了两类广义Jacobi序列的自相关特性,给出了它们的自相关函数的取值,结论表明:两类广义Jacobi序列都具有良好的自相关特性。     

高阶广义(3 + 1)维Kadomtsov-Petviashivilli方程新的显式解

利用广义的代数方法,研究了高阶广义（3+1）维Kadomtsov-Petviashivilli方程,得到了许多新的显式解,这些解包括椭圆函数解,双曲函数解,三角函数解等。     

Scattering from finite by infinite arrays of slots in a thinconducting wedge

The radar scattering from a finite by infinite array of slots cut into a thin conducting wedge is considered. The wedge is formed by taking a thin ground plane and applying a bend to create a sharp edge which is parallel to the columns of slots in the infinite axis. Results are derived for thin linear slots whose major axes are either parallel or perpendicular to the edge. A hybrid moment method and geometrical theory of diffraction approach is used, with magnetic current expansion functions defined using Floquet's theorem on single columns of slots. Predictions generally agree with scattering measurements of finite by finite array physical models with monostatic patterns taken in a plane orthogonal to the sharp edge     

Restructured recursive DCT and DST algorithms

The discrete cosine transform (DCT) and the discrete sine transform (DST) have found wide applications in speech and image processing, as well as telecommunication signal processing for the purpose of data compression, feature extraction, image reconstruction, and filtering. In this paper, we present new recursive algorithms for the DCT and the DST. The proposed method is based on certain recursive properties of the DCT coefficient matrix, and can be generalized to design recursive algorithms for the 2-D DCT and the 2-D DST. These new structured recursive algorithms are able to decompose the DCT and the DST into two balanced lower-order subproblems in comparison to previous research works. Therefore, when converting our algorithms into hardware implementations, we require fewer hardware components than other recursive algorithms. Finally, we propose two parallel algorithms for accelerating the computation     

基于广义互质双平行阵列的二维DOA估计方法

对于给定阵元数目的 传统双平行均匀线阵,由于其阵列布局受到空间采样定理限制,阵列孔径不能有效扩展,二维波达方向(DOA)估计的精度和自由度难以得到有效提升.提出一种基于广义互质双平行阵列的二维DOA估计方法.采用两个互相平行的广义互质线阵进行虚拟扩展得到含有较多虚拟阵元的差分优化阵列,并利用该虚拟阵列的协方差信息和互协...     

Large parallel processing revisited: a second tutorial

An efficient parallel LU algorithm that is suitable for a local-memory MIMD (multiple input multiple data) computer, such as an array of transputers, is described. A graphical approach is used to elucidate the algorithm. The results of a theoretical timing analysis are given. Some methods for reducing the communication load, by intelligent exploitation of the capabilities of certain parallel hardware, are described. Timing results for a code implementing the algorithm on a transputer array are given and compared to results for a parallel conjugate-gradient algorithm. The stability of LU decomposition is discussed. Pivoting is briefly reviewed, although the algorithm described does not implement this, at present. PARNEC, a parallel version of NEC2, is described. The parallel generation of the matrix elements is discussed, and a solution for NEC2 presented. Results for a preliminary test of the accuracy of PARNEC are given. The choice of a CG or LU solver for the solution of the system of linear equations generated by method-of-moment formulation and new parallel hardware are discussed     

A splitting method for total least squares color image restoration problem

Color image restoration is an important problem in image processing. Using the structured total least squares (STLS) for fidelity term of the restoration process gives better results in comparison with the least squares (LS) approach. The main drawback of the STLS approach is its complexity. To overcome this issue, in this paper by an appropriate transformation the color image restoration is substituted with two smaller subproblems corresponding to smooth and oscillatory parts of the image. The first and second subproblems are modeled via STLS and LS approaches, respectively. We show that the proposed method is faster than STLS and gives competitive solutions with it. Also, we demonstrate that Haar wavelet perseveres the structure of the blurring operator, which causes a considerable reduction in computational and storage complexity of the proposed method.