An ESPI apparatus with multichannel data acquisition

An ESPI (Electronic Speckle Pattern Interferometry) apparatus employing a linear photodiodes array for multichannel data acquisition is described. The technique is applied for measurements of normal displacements of surfaces when time and space resolutions are required.     

Precomputed compressive sensing for light transport acquisition

In this article, we propose an efficient and accurate compressive-sensing-based method for estimating the light transport characteristics of real-world scenes. Although compressive sensing allows the efficient estimation of a high-dimensional signal with a sparse or near-to-sparse representation from a small number of samples, the computational cost of the compressive sensing in estimating the light transport characteristics is relatively high. Moreover, these methods require a relatively smaller number of images than other techniques although they still need 500–1000 images to estimate an accurate light transport matrix. Precomputed compressive sensing improves the performance of the compressive sensing by providing an appropriate initial state. This improvement is achieved in two steps: 1) pseudo-single-pixel projection by multiline projection and 2) regularized orthogonal matching pursuit (ROMP) with initial signal. With these two steps, we can estimate the light transport characteristics more accurately, much faster, and with a lesser number of images.     

Photonics-assisted compressive sampling system for wideband spectrum sensing

Compressive sampling(CS) has attracted considerable attention in microwave and radio frequency(RF) fields in recent years. It enables the acquisition of high-frequency signals at a rate much smaller than their Nyquist rates.Combined with photonics technology, traditional CS systems can significantly enlarge their operating bandwidth, which offers great potential for spectrum sensing in cognitive radios. In this Letter, we review our recent work on photonic CS systems for wideband spectrum sensing. First, a proof-of-concept photonics-assisted CS system is demonstrated; it is capable of acquiring numerous radar pulses in an instantaneous bandwidth spanning from 500 MHz to 5 GHz with a 500-MHz analog-to-digital converter(ADC). To further reduce the acquisition bandwidth, multi-channel photonics-assisted CS systems are proposed for the first time, enabling the acquisition of multi-tone signals with frequencies up to 5 GHz by using 120-MHz ADCs. In addition, the system bandwidth is increased from 5 to 20 GHz by employing time-interleaved optical sampling.     

On the use of multichannel data acquisition of impedance spectra

Impedance spectroscopy is a powerful technique for electrical and electrochemical characterisation of ionic conductors and other electroceramics. Thus, one might tempted to use multichannel data acquisition to allow the utilisation of expensive LCR meters for simultaneous measurements. This work shows results for YSZ and strontium titanate ceramics, obtained with a multi-channel data acquisition system, to demonstrate the limitations of this approach and the applicability of some corrections. Impedance spectra are affected under multi-channel conditions, mainly in the high frequency contributions, and this is approximately described by a stray capacitance. The bulk contribution of the spectra is most affected. Contributions of internal interfaces (e.g. grain boundaries) are relatively well characterised, mainly after the proposed corrections. The characterisation of electrode processes is not affected. Paper presented at the 9th EuroConference on Ionics, Ixia, Rhodes, Greece, Sept. 15–21, 2002.     

Signal-to-noise ratio of Raman signal measured by multichannel detectors

Raman spectroscopy has been widely used to characterize the physical properties of two-dimensional materials(2 DMs). The signal-to-noise ratio(SNR or S/N ratio) of Raman signal usually serves as an important indicator to evaluate the instrumental performance rather than Raman intensity itself. Multichannel detectors with outstanding sensitivity, rapid acquisition speed and low noise level have been widely equipped in Raman instruments for the measurement of Raman signal. In this mini-review, we first introduce the recent advances of Raman spectroscopy of 2 DMs. Then we take the most commonly used CCD detector and IGA array detector as examples to overview the various noise sources in Raman measurements and analyze their potential influences on SNR of Raman signal in experiments. This overview can contribute to a better understanding on the SNR of Raman signal and the performance of multichannel detector for numerous researchers and instrumental design for industry, as well as offer practical strategies for improving spectral quality in routine measurement.     

Enhancing the acquisition efficiency of fast magnetic resonance imaging via broadband encoding of signal content

Current efficient magnetic resonance imaging (MRI) methods such as parallel-imaging and k-t methods encode MR signals using a set of effective encoding functions other than the Fourier basis. This work revisits the proposition of directly manipulating the set of effective encoding functions at the radiofrequency excitation step in order to increase MRI efficiency. This approach, often termed "broadband encoding," enables the application of algebraic matrix factorization technologies to extract efficiency by representing and encoding MR signal content in a compacted form. Broadband imaging equivalents of fast multiecho, parallel and k-t MRI are developed and analyzed. The potential of these techniques to increase the time efficiency of data acquisition is experimentally verified on a commercial MRI scanner using simple spin-echo imaging. A three-dimensional gradient-echo dynamic imaging application that demonstrates the potential benefits of this approach compared to the present state of the art for certain applications is also presented.     

Structured sublinear compressive sensing via belief propagation

Compressive sensing (CS) is a sampling technique designed for reducing the complexity of sparse data acquisition. One of the major obstacles for practical deployment of CS techniques is the signal reconstruction time and the high storage cost of random sensing matrices. We propose a new structured compressive sensing scheme, based on codes of graphs, that allows for a joint design of structured sensing matrices and logarithmic-complexity reconstruction algorithms. The compressive sensing matrices can be shown to offer asymptotically optimal performance when used in combination with orthogonal matching pursuit (OMP) methods. For reduced-complexity greedy reconstruction schemes, we propose a new family of list-decoding belief propagation algorithms, as well as reinforced and multiple-basis belief propagation (BP) algorithms. Our simulation results indicate that reinforced BP CS schemes offer very good complexity–performance tradeoffs for very sparse signal vectors.     

Off-shell πN amplitudes via a multichannel separable potential

The off-shell pion-nucleon transition matrix is a basic ingredient in theories of pion-nuclear interactions which, in the absence of fundamental theory of πN dynamics, must be obtained by a phenomenological extrapolation from the available on-shell data. As one means of performing such an extrapolation, we explore a multichannel separable potential model with the property that the off-shell elastic scattering amplitude is generated directly from the measured elastic-channel phase shifts. The off-shell πN partial-wave transition amplitudes determined by this procedure are compared with those calculated by Landau and Tabakin using a one-channel absorptive separable potential. We find that the absorptive separable potential approach provides a physically unreasonable off-shell extrapolation at energies where the on-shell amplitude is highly inelastic, and show that the difficulty is a direct consequence of the one-channel nature of that method. The multichannel extrapolation is free of these difficulties.     

Spatial interpolation of HRTFs and signal mixing for multichannel surround sound

From the point of spatial sampling, spatial interpolation of HRTFs (head-related transfer functions) and signal mixing for multichannel (surround) sound are analyzed. First, it is proved that they are mathematically equivalent. Different methods for HRTFs interpolation are equivalent to different signal mixing methods for multichannel sound. Then, a stricter derivation for the signal mixing of multichannel sound and the law of sine for stereophonic sound is given. It is pointed out that trying to reconstruct lateral HRTFs by adjacent linear interpolation is wrong. And for accurate sound image localization, the conventional equation of adjacent linear interpolation of HRTFs is revised. At last, it is also pointed out that some methods used in the analysis of HRTFs and multichannel sound can be used for reference mutually.     

Efficient measurement of quantum dynamics via compressive sensing

The resources required to characterize the dynamics of engineered quantum systems--such as quantum computers and quantum sensors--grow exponentially with system size. Here we adapt techniques from compressive sensing to exponentially reduce the experimental configurations required for quantum process tomography. Our method is applicable to processes that are nearly sparse in a certain basis and can be implemented using only single-body preparations and measurements. We perform efficient, high-fidelity estimation of process matrices of a photonic two-qubit logic gate. The database is obtained under various decoherence strengths. Our technique is both accurate and noise robust, thus removing a key roadblock to the development and scaling of quantum technologies.     

Detecting low-rank clusters via random sampling

We present an algorithm for detecting a low-rank cluster of vectors from within a much larger group of vectors. This algorithm relies on a basic geometric property of high-dimensional space: Most of the volume of a typical eccentric ellipsoid is confined to relatively few orthants within the ambient space. This simple fact can be used to quickly detect a collection of vectors with low numerical rank from amongst a larger group of vectors with higher numerical rank.     

GPS最优压制式干扰信号研究

针对GPS最优干扰信号评估方法欠缺的问题,提出了利用误码率判断最优干扰信号的方法。建立了卫星导航接收机模型和基于中频信号的误码率模型,研究不同干扰环境下接收机的误码率。通过改变干扰信号功率得到误码率与干信比的关系曲线,比较不同干扰信号同干信比下的误码率,得到最优干扰信号。通过实验验证,相同环境下,伪码相关干扰信号效果最优,为卫星导航信号干扰设备的研发及设计提供了依据。     

Quantum formalism via signal analysis

The general properties of signals permit a nonaxiomatic reconstruction of the quantum probability formalism independent of the standard Copenhagen interpretation of quantum mechanics. Performance standards are specified for candidate clock, signaller, and reflector devices, and it is shown that the resulting formalism forces identification of a probability- or intensity-like structure as the absolute square of an amplitude, the relative phases of amplitudes appearing explicitly in the probability composition law. Inequalities are produced which on one interpretation reduce to the Heisenberg relations, but it is pointed out that this reconstruction disqualifies position as an observable property of a signal.     

基于压缩感知理论的~(252)Cf源中子脉冲信号分析

针对252Cf源驱动核材料产生裂变中子脉冲信号具有脉冲序列特殊的"0,1"稀疏结构之特点,采用压缩感知理论,通过巧妙引入图论中的二分图模型,同时结合二分图的最小覆盖性质,适当添加约束条件,构建了稀疏均匀的观测矩阵。研究结果表明,利用压缩感知理论对"0,1"中子脉冲序列特殊稀疏结构的信号重构算法不仅可行,而且还获得了优于l1范数最小化方法重构结果,这对252Cf驱动核材料的中子脉冲信号分析与处理提供了一种新的途径或方法。     

稀疏正交联合约束多通道非负矩阵分解声信号分离算法

针对复杂环境下多通道声信号分离问题,提出稀疏正交联合约束多通道非负矩阵分解声信号分离方法。首先设计基于多通道扩展坂仓斋藤(Itakura-Saito,IS)散度的稀疏正交联合约束项构造代价函数,给出信号稀疏和信号正交约束辅助函数,实现代价函数最小化求解。然后通过迭代更新规则设计,得到稀疏正交优化的多通道非负矩阵分解基矩阵和系数矩阵,讨论了稀疏正交约束对基矩阵和系数矩阵稀疏性与连续性影响。最后基于多通道信号空间特性,进行了非负矩阵分解基聚类以获得多通道非负矩阵分解声信号的分离结果。双通道音频数据与四通道声学目标分离实验数据测试表明,对音频数据,所提算法在性能指标信号失真比(SDR)上提高了0.84dB,对于直升机声源数据,所提算法在SDR上提高了4.53dB。     

多通路空间声的前方四扬声器局域Ambisonics信号馈给法*

典型的多通路空间声扬声器布置一般包含水平面左前、右前,高仰角左前上、右前上四个方向的扬声器。 本文提出一种利用该四个扬声器产生前方水平与垂直方向虚拟源的一阶局域Ambisonics 信号馈给法。该信号馈给法是通过对目标和重放声场进行球谐函数展开并取一阶近似得到。采用简化的头部模型和精确的头相关传输函数模型分析表明,一阶局域Ambisonics 信号馈给法可以产生合适的低频听觉定位因素,包括双耳时间差及其随头部转动的动态变化。虚拟源定位实验结果表明,该方法可以在扬声器布置的范围内,甚至在略超出扬声器布置的范围内产生不同方位角和仰角的虚拟源。因而本文的方法可用在多通路空间声重放中产生与图像配合的虚拟源定位效果。     

头相关传输函数空间采样、插值与环绕声重放

从空间方向采样的角度对头相关传输函数(HRTF)空间插值、多通路环绕声重放进行了分析,证明了它们在数学上是完全等价的,不同的HRTF空间插值方法对应于不同的多通路环绕声信号馈给,并给出了多通路环绕声信号馈给以及立体声的正弦定理更严格的数学推导。分析指出企图用相邻线性插值的方法得到侧向的HRTF是错误的,并从保证声像定位的角度,对现有的HRTF相邻线性插值公式进行了修正。分析最后指出,HRTF以及虚拟声的许多分析方法可与多通路环绕声相互借鉴。     

Experimental quantum state tomography via compressed sampling

A fundamental difficulty in demonstrating quantum state tomography is that the required resources grow exponentially with the system size. For pure states and nearly pure states, the task of tomography can be more efficient. We proposed two methods for state reconstruction, by (1) minimizing entropy and (2) maximizing likelihood. The algorithm of compressed sampling is employed to solve the optimization problem. Experiments are demonstrated considering 4-qubit photonic states. The results show that (1) much fewer measurements than the standard tomography are sufficient to obtain high fidelity, and (2) the method of maximizing likelihood is more accurate and noise robust than the original reconstruction method of compressed sampling. Furthermore, the physical meaning of the methods of minimizing entropy and maximizing likelihood is clear.