Penalized weighted least-squares image reconstruction for positron emission tomography

Presents an image reconstruction method for positron-emission tomography (PET) based on a penalized, weighted least-squares (PWLS) objective. For PET measurements that are precorrected for accidental coincidences, the author argues statistically that a least-squares objective function is as appropriate, if not more so, than the popular Poisson likelihood objective. The author proposes a simple data-based method for determining the weights that accounts for attenuation and detector efficiency. A nonnegative successive over-relaxation (+SOR) algorithm converges rapidly to the global minimum of the PWLS objective. Quantitative simulation results demonstrate that the bias/variance tradeoff of the PWLS+SOR method is comparable to the maximum-likelihood expectation-maximization (ML-EM) method (but with fewer iterations), and is improved relative to the conventional filtered backprojection (FBP) method. Qualitative results suggest that the streak artifacts common to the FBP method are nearly eliminated by the PWLS+SOR method, and indicate that the proposed method for weighting the measurements is a significant factor in the improvement over FBP.     

A unified approach to three eigendecomposition methods forfrequency estimation

The authors present a unified approach to three eigendecomposition-based methods for frequency estimation in the presence of noise. These are the Tufts-Kumaresan (TK) method, the minimum-norm (MN) method, and the total least squares (TLS) method. It is shown that: (1) the MN method is a modified version of the TK method; (2) the TLS method is a generalization of the MN method; (3) the TLS solution vector can be expressed in matrix form, and an alternative way of computing it is presented; (4) the MN and the TLS methods exhibit some improvement over the TK method     

Group decorrelation enhanced subspace method for identifying FIR MIMO channels driven by unknown uncorrelated colored sources

Identification of finite-impulse-response (FIR) and multiple-input multiple-output (MIMO) channels driven by unknown uncorrelated colored sources is a challenging problem. In this paper, a group decorrelation enhanced subspace (GDES) method is presented. The GDES method uses the idea of subspace decomposition and signal decorrelation more effectively than the joint diagonalization enhanced subspace (JDES) method previously reported in the literature. The GDES method has a much better performance than the JDES method. The correctness of the GDES method is proved assuming that 1) the channel matrix is irreducible and column reduced and 2) the source spectral matrix has distinct diagonal functions. However, the GDES method has an inherent ability to trade off between the required condition on the channel matrix and that on the source spectral matrix. Simulations show that the GDES method yields good results even when the channel matrix is not irreducible, which is not possible at all for the JDES method.     

Blind identification of multi-input multi-output system usingminimum noise subspace

This article presents a new subspace based method for blind identification of a p-input/q-output system, where q>p. This method exploits a minimum noise subspace (MNS) to retrieve the system impulse responses. The MNS method requires only q-p noise vectors as opposed to all noise vectors needed by a standard subspace (SS) method. It is shown that the MNS can be obtained in a parallel structure from a set of tuples (combinations) of system outputs that form a properly connected sequence (PCS). The PCS exploits with minimum redundancy the diversity among system outputs. The MNS method is much more efficient in computation than the SS method, although the former is less robust to noise than the latter     

降低可见光DCO-OFDM系统峰均比的DCT-GCS方法

为了克服现有降低OFDM峰值平均功率比的方法在可见光通信中效果不好的问题,通过分析发现DCO-OFDM系统输入序列的共轭对称形式增强了序列的相关性,使传统方法的PAPR抑制性能有明显下降,所以提出了离散余弦变换(DCT)与分组循环移位(GCS)结合的降低系统PAPR的方法。该方法中的分组循环移位能够在DCT的基础上降低输入序列的相关性,使系统输出信号具有更低的PAPR。仿真结果表明:提出的方法比仅采用DCT或者GCS能够更好地抑制系统的PAPR。在CCDF=10-4时,DCT-GCS方法使系统的PAPR下降了5.4dB。DCT-GCS具有较低的PAPR,且计算复杂度要远远低于PTS和SLM方法。      

A low-complexity zero-forcing CFO compensation scheme for OFDMA uplink systems

Similar to the conventional orthogonal frequencydivision multiplexing (OFDM) system, an OFDM multiple access (OFDMA) system will have a carrier frequency offset (CFO) problem. Since CFOs of all users are different, CFO compensation in the OFDMA uplink system is much more involved. A simple, yet efficient, method is the zero-forcing (ZF) compensation method. However, it involves an inverse of an N × N CFO-induced ICI matrix, where N is the number of subcarriers. Thus, the complexity can become very high when N is large, a case commonly seen in OFDMA systems. In this work, we propose a low-complexity ZF method to overcome the problem. The main idea is to use Newton's method to solve matrix inversion iteratively. We explore the structure of the CFOinduced ICI matrix and develop a method that can implement Newton's method with fast Fourier transforms (FFTs). As a result, the required computational complexity is significantly reduced from O(N³) to O(2N log₂N). Simulations show that, with only three iterations, the proposed method can have similar performance to the direct ZF method.     

Nested Newton's method for ICA and post factor analysis

Two distinct topics are dealt with. First, a new method for independent component analysis (ICA) has been constructed that exploits the invariance of criteria under component-wise scaling, which is intrinsic to ICA. This practical and simple ICA method is called the nested Newton's method. When the number of the channel of observation is less than a certain level, factor analysis (FA) is ineffective (bound for FA). The target of this paper is these cases. Three of many concrete advantages of the nested Newton's method are addressed. i) It is robust against Gaussian noise and outperforms existing methods, such as JADE and Fast ICA, especially under Gaussian noise conditions. ii) It is highly stable globally. iii) Each step resolves itself into two-dimensional (2-D) matrix problems. There is thus no need to deal with gigantic matrices, which means that fewer computational resources are required. Second, a method called "post factor analysis (post-FA)" is described that is aimed to be useful as post-processing for ICA. Although it is functionally similar to conventional FA, post-FA is a completely new method and is more powerful than conventional FA in compensation for its stronger assumption that there are mutually independent sources behind observations. By fully making use of this assumption, post-FA is capable of estimating the noise variance beyond the known limit for FA. Furthermore, it improves the accuracy of ICA to a considerable extent. Any ICA algorithm without prewhitening (pre-WH) or pre-factor-analysis (pre-FA) can be used for preprocessing, although the nested method is a good candidate.     

Determining Q using S parameter data

A method is presented for determining frequency selectivity (Q) of a network using scattering (S) parameter data, data that is readily available from network measurements or analysis. The approach is based on a formulation for Q that uses the change in reactance of the resonant circuit with frequency. The method yields accurate Q results for both high and low Q resonators. Furthermore, the method is easy to implement and to understand. An example is given for calculating the Q of a tapped-stub resonator. Using this example, the new method is compared to the critical points (CP) method, an approach based on a Foster network type of formulation     

Numerical method for calculating surface current density on a two-dimensional scatterer with smooth contour

A numerical method is presented for finding the surface current density on a two-dimensional smooth scatterer. This method is an improved version of a method which one of the authors presented as an adjoint method to the conventional mode-matching method (MMM) for finding the scattered field. After formulating the problem, we interpret the method being adjoint to the conventional mode-matching method and show that the method yields a sequence of approximate current densities converging to the true density in the mean squares sense. Next we propose the improved method and prove the fact that this method yields a sequence of approximate solutions which converges to the true density uniformly on the contour of the scatterer. We then state that the method is an adjoint one to the mode-matching method with a smoothing procedure (SP) which we proposed as a powerful numerical method for the scattered field. Numerical results of some sample calculation are attached to show the effectiveness of the new method.     

An iterative current-based hybrid method for complex structures

This paper presents a general unified hybrid method for radiation and scattering problems such as antennas mounted on a large platform. The method uses a coupled electric-field integral equation (EFIE) and magnetic-field integral equation (MFIE) formulation, referred to as the hybrid EFIE-MFIE (HEM), in which the EFIE and MFIE are applied to geometrically distinct regions of an object. The HEM is capable of modeling arbitrary three-dimensional (3-D) metallic structures, including wires and both open and closed surfaces. We show that current-based hybrid techniques that utilize physical optics (PO) are an approximation of the HEM formulation. A numerical solution procedure is given that combines the moment method (EFIE) with an iterative Neumann series technique (MFIE). This permits one to effectively utilize the PO approximation when appropriate, and provides a general and systematic mechanism to correct the errors introduced by PO. Consequently, the HEM overcomes the inherent limitations of hybrid techniques which rely upon ansatz-based improvements of PO. The method is applied to the problem of radiation from objects that can be modeled using wires and metallic surfaces as fundamental elements. A representative example is given to demonstrate that the method can handle the difficult problem of a parasitic monopole located in the deep shadow region     

A two-dimensional time-domain finite element formulation for periodic structures

A formulation is presented for a two-dimensional time-domain finite-element method (FEM-TD) that incorporates periodic boundaries. The specifics of the method are shown for scattering problems, but it should be straightforward to extend it to radiation problems. The method solves for a transformed field variable (instead of solving directly for the electric field) in order to easily enable periodic boundary conditions in the time domain. The accuracy and stability of the method is demonstrated by a series of examples where the new formulation is compared with reference solutions. Very accurate results are obtained when the excitation (frequency range) and the geometry are such that no higher order Floquet modes are present. The accuracy is degraded in the presence of higher order modes due to the rather simple absorbing boundary condition that is used with the present formulation. The method is found to be stable even for angles of incidence close to grazing.     

PC-based frame synchronization method for byte-misaligned stream

As the traditional character-oriented frame synchronization methods are no longer applicable to the byte-misaligned stream, and the efficiency of the bit-oriented method is hardly acceptable, a character-oriented bit-shift stream frame synchronization （COBS-FS） method is presented. In order to measure the performance of the given method, a bit-oriented frame synchronization method, based on Knuth-Morris-Pratt （KMP-FS） algorithm, is used for comparison. It is proven in theory that the COBS-FS has a much lower cost in frame header searching. Experiment shows that the COBS-FS method is with better performance than the KMP-FS algorithm in both computational effort and execution time.     

A novel wideband DOA estimator based on Khatri-Rao subspace approach

A novel DOA estimation method for uncorrelated wideband sources named focusing Khatri-Rao subspace method (FKR) is proposed based on coherent signal-subspace method (CSM) and Khatri-Rao (KR) subspace. Compared with the conventional CSM that simply averages the covariance matrices of different frequency bins after focusing, FKR transforms the covariance matrices into a higher dimensional matrix through KR product. This method has three major advantages: (1) it achieves a higher resolution than CSM, (2) the root mean square error of DOA estimation from FKR is smaller than that of CSM when the initial angles are inaccurate and (3) it performs well even when the number of sensors is reduced to about half of the sources. The performance of the FKR method is demonstrated and analyzed through the computer simulations.     

Equivalence between voltage-processing methods and discreteorthogonal Legendre polynomial (DOLP) approach

There are three methods for solving the least-squares estimation (LSE) problem. (1) the power method; (2) the voltage-processing method (square-root method); and (3) the discrete orthogonal Legendre polynomial (DOLP) method. The first involves a matrix inversion and is sensitive to computer round-off errors. The second and third do not require a matrix inversion and are not as sensitive to computer round-off errors. It is shown that the voltage-processing LSE methods (Givens, Householder, and Gram-Schmidt) become the discrete orthogonal Legendre polynomial (DOLP) LSE method when the data can be modeled by a polynomial function and the times between measurements are equal. Furthermore, when the data can be modeled by a polynomial function and the time between measurements are equal, the DOLP is the preferred method because it does not require an orthonormal transformation and it does not require the back-substitution method     

Optimization of Fiber Bragg Gratings Using a Hybrid Optimization Algorithm

A new hybrid optimization algorithm is proposed for the design of a fiber Bragg grating (FBG) with complex characteristics. The hybrid algorithm is a two-tier search that employs a global optimization algorithm (i.e., the staged continuous tabu search (SCTS) algorithm) and a local optimization method (i.e., the quasi-Newton method). First, the SCTS global optimization algorithm is used to find a "promising" FBG structure that has a spectral response as close as possible to the targeted spectral response. Then, a local optimization method, namely, the quasi- Newton method, is applied to further optimize the promising FBG structure obtained from the SCTS algorithm to arrive at a targeted spectral response. To demonstrate the effectiveness of the method, the design and fabrication of an optical bandpass filter are presented.     

The Need of Terahertz Cameras for Standardizing Sensitivity Measurements

The applicability of a blackbody source to sensitivity measurements and calibration of an uncooled Terahertz (THz) focal plane array (FPA) is discussed, but the combination of a blackbody source and a band-pass filter may not be suitable for these purposes. Two ways to measure the minimum detectable power (MDP) of uncooled THz-FPAs are described and compared when used with strong THz sources such as a quantum cascade laser (QCL). The MDP is defined as the radiant power that produces a signal-to-noise ratio of unity in the output of a THz imager that uses a THz-FPA operating at a TV frame rate. One method (method 1) is based on the hypothesis that the beam pattern of the THz source is close to a Gaussian pattern. In another method (method 2), the signal level of the background in an image that does not contain a THz source is subtracted from the signal of the image. While method 2 is more flexible, how large the signals coming from THz source should be, as compared with the noise level, remains to be defined. Finally, based on issues with the current non-uniformity correction (NUC) technique, specifications are proposed for THz source power and wobbling technique to obtain uniform illumination for an ideal NUC technique.     

A novel zero-forcing precoding method for multi-cell MIMO systems

Precoding methods at the Base Station (BS) can be used to deal with the inter-cell interference and improve the signal quality of the user especially at the cell edge. In this paper, a novel Zero-Forcing (ZF) precoding method is proposed and investigated for multi-cell Multi-Input Multi-Output (MIMO) systems. We propose a relaxed ZF precoding method by relaxing the ZF criterion to some degree so that the inter-cell interference may not be zero. Complexity analysis shows that compared with the conventional ZF method, the additional computation complexity for the proposed method is trivial. Simulation results show that the proposed relaxed ZF method has better performance than the conventional ZF method in terms of the sum-rate, especially at low Signal to Noise Ratio (SNR).     

A parallel finite-element tearing and interconnecting algorithm forsolution of the vector wave equation with PML absorbing medium

A domain decomposition method based on the finite-element tearing and interconnecting (FETI) algorithm is presented for the solution of the large sparse matrices associated with the finite-element method (FEM) solution of the vector wave equation. The FETI algorithm is based on the method of Lagrange multipliers and leads to a reduced-order system, which is solved using the biconjugate gradient method (BiCGM). It is shown that this method is highly scalable and is more efficient on parallel platforms when solving large matrices than traditional iterative methods such as a preconditioned conjugate gradient algorithm. This is especially true when a perfectly matched layer (PML) absorbing medium is used to terminate the problem domain     

基于约束总体最小二乘方法的到达时差到达频差无源定位算法

两步加权最小二乘方法(two-stage WLS)是求解TDOA/FDOA无源定位问题的经典线性方法,但也存在着定位偏差和均方误差对测量噪声的适应能力较差的缺点。该文根据TDOA/FDOA的伪线性定位方程组特点,将其建立为一种带约束条件的约束总体最小二乘(CTLS)模型,并采用拉格朗日乘子法求解带约束条件的CTLS问题,建立了几种最小二乘类定位方法的统一解,从而将约束加权最小二乘(CWLS)定位解和约束最小二乘(CLS)定位解变为该文CTLS定位解的特例。仿真表明,该文方法比两步加权最小二乘方法具有更低的均方误差,并能够有效减小定位偏差,因而具有更好的测量噪声适应能力。     

PAPR Reduction in OFDM Systems Based on Autoregressive Filtering

Orthogonal frequency division multiplexing (OFDM) has a very high peak-to-average power ratio (PAPR) that causes a severe nonlinear distortion in practical hardware implementation of high power amplifiers (HPA). In this article, a new PAPR reduction method is proposed based on autoregressive (AR) error filtering. This method proposes the use of signal whitening property of error filtering as a preprocessing step to remove the predictable content of stationary stochastic processes which can reduce the autocorrelation of input data sequences and is shown to be a very effective solution for the PAPR problem in OFDM systems. It is shown that the proposed method can achieve a significant reduction in PAPR without degrading the error performance or power spectral levels. It is also shown that the proposed method is applicable to any modulation scheme and can work for any number of subcarriers under both additive white Gaussian noise and wireless Rayleigh fading channel.