Nonparametric polyspectral estimators for k-th-order (almost) cyclostationary complex processes

Higher-order almost cyclostationary complex processes are complex random signals with almost periodically time-varying statistics, which is important to the research of non-Gaussian signals in information system. In this paper, smoothed polyperiodograms are proposed for related to cyclic polyspectral estimation and are shown to be consistent and asymptotically complex normal. Asymptotic covariance expressions are derived along with their computable forms.     

复高阶周期平稳信号的非参数多谱估计

本文研究利用平滑周期图作为离散时间k阶复周期平稳过程k阶循环谱估计的相容性和渐近复正态性,并导出了其渐近协方差表达式.     

复循环平稳的非平稳信号的非参数谱估计

复准循环平稳信号为具有准周期时变统计特性的复随机信号,它对研究信息系统中的一些非高斯过程有重要意义。本文提出了平滑周期图作为离散时间复循环平稳过程的循环谱估计,并从理论上证明了该估计为相容估计,还导出了其渐近协方差表达式。     

NONPARAMETRIC SPECTRAL ESTIMATORS FORSECOND-ORDER (ALMOST) CYCLOSTATIONARYCOMPLEX PROCESSES

Second-order almost cycloststionary complex processes are complex random signals with almost periodically time-varying statistics. Smoothed periodograms are proposed for related to cyclic spectral estimation and are shown to be consistent. Asymptotic covariance expressions are derived along with their computable forms.     

Test signals with multilevel subcarriers as applied to satellite radio-navigation systems

Noise-like meander signals are proposed to generate on the basis of multilevel pseudorandom sequences making it possible to include multilevel subcarriers. It is demonstrated that such signals are characterized by the pronounced central region of the principal peak of the real part of their complex autocorrelation function and its other values remain almost identical in the time interval corresponding to the principal correlation peak. They are several times less than those of binary offset carrier modulated signals. It is established that the selection of a subcarrier phase structure makes it possible to more flexibly control the shape of the power spectral density of signals and its arrangement on the frequency in comparison with BOC signals.     

Fast computation of the discrete Fourier transform of real data

Fast algorithms for the computation of the discrete Fourier transform (DFT) of real signals are important since the signals in practical situations are mostly real. The more efficient algorithms for real data are those that are derived from the algorithms for complex data. So far, all such algorithms use a real array to store the data. However, as the data values are real and their transform values are mostly complex, two possible data structures can be used for these algorithms: real or complex. DFT algorithms for real data that use a complex array for storing both the real data and their transform values are derived from the Cooley-Tukey radix-2 algorithm for complex data. This approach reduces the number of bit-reversal and array-index updating operations, eliminates independent data-swapping operations, and yields a computational structure that is almost as regular as that of the algorithms for complex data. Detailed derivations of the proposed algorithms for the computation of both the DFT of real data and the inverse DFT of the transform of real data, as well as their computational complexities, are presented. A C-language program of one of the proposed algorithms is given, illustrating the use of all the features of the new approach in software implementation. Comparison results are included to show that the proposed algorithms are faster and simpler than the real-valued split-radix and other algorithms     

一种复杂波形信号产生器的设计与实现

介绍了一种复杂波形信号产生器的设计与实现,采用高速直接数字频率合成器产生各种复杂波形信号,并且通过微波宽带倍频器对DDS产生的复杂波形信号进行倍频,从而实现对DDS输出信号带宽的扩展,最终产生各种宽带复杂波形信号。文中介绍了设计方案与实现方法,并研制出工程样机。最终设计的复杂波形信号产生器能够实现线性调频、非线性调频、相位编码等多种复杂波形信号,输出信号带宽最高可达1 GHz。     

Nonparametric polyspectral estimators for kth-order (almost)cyclostationary processes

Second- and higher-order almost cyclostationary processes are random signals with almost periodically time-varying statistics. The class includes stationary and cyclostationary processes as well as many real-life signals of interest. Cyclic and time-varying cumulants and polyspectra are defined for discrete-time real kth-order cyclostationary processes, and their interrelationships are explored. Smoothed polyperiodograms are proposed for cyclic polyspectral estimation and are shown to be consistent and asymptotically normal. Asymptotic covariance expressions are derived along with their computable forms. Higher than second-order cyclic cumulants and polyspectra convey time-varying phase information and are theoretically insensitive to any stationary (for nonzero cycles) as well as additive cyclostationary Gaussian noise (for all cycles)     

Segmentation and classification of dot and non-dot-like fluorescence in situ hybridization signals for automated detection of cytogenetic abnormalities.

Signal segmentation and classification of fluorescence in situ hybridization (FISH) images are essential for the detection of cytogenetic abnormalities. Since current methods are limited to dot-like signal analysis, we propose a methodology for segmentation and classification of dot and non-dot-like signals. First, nuclei are segmented from their background and from each other in order to associate signals with specific isolated nuclei. Second, subsignals composing non-dot-like signals are detected and clustered to signals. Features are measured to the signals and a subset of these features is selected representing the signals to a multiclass classifier. Classification using a naive Bayesian classifier (NBC) or a multilayer perceptron is accomplished. When applied to a FISH image database, dot and non-dot-like signals were segmented almost perfectly and then classified with accuracy of approximately 80% by either of the classifiers.     

Multitone signals with low crest factor

After an introductory discussion of real-valued and complex signals, it is shown that minimizing the crest factor (CF) of multitone signals is closely related to the construction of complex sequences with low sidelobes in their aperiodic autocorrelation function. Inspired by this observation, a lower bound on the achievable CF is derived. Four differing algorithms for the reduction of the CF of complex multitone signals are compared with each other by computer simulation. The preferred algorithm is presented in detail, and its convergence is proven. Examples of multitone signals with up to 15 tones and lower CF than previously reported in the literature are given     

Spectral Relations for Multidimensional Complex Improper Stationary and (Almost) Cyclostationary Processes

We study continuous-time multidimensional wide- sense stationary (WSS) and (almost) cyclostationary processes in the frequency domain. Under the assumption that the correlation function is uniformly continuous, we prove the existence of a unique sequence of spectral measures, which coincide with the restrictions to certain subdiagonals of the spectral measure in the strongly harmonizable case. Moreover, the off-diagonal measures are absolutely continuous with respect to the diagonal measure. As a consequence, for strongly harmonizable scalar improper almost cyclostationary processes, we obtain representation formulas for the components of the complementary spectral measure and the off-diagonal components of the spectral measure, in terms of the diagonal component of the spectral measure. We apply these results to analytic signals, which produces sufficient conditions for propriety for almost cyclostationary analytic signals.     

Use of Ferrites for Absorption of Electromagnetic Waves

Ferrites have been known as good absorbers of electromagnetic waves for some forty years. They are very effective against the conventional radar using signals with small relative bandwidth, but they should have almost no effect on radar signals with large relative disappointment if this fact is overlooked.     

The bond between causal complex cepstra and Sheffer polynomials

A strong bond is established between causal complex cepstra and Sheffer polynomials. This bond results in the generation of parametric classes of discrete-time signals and their associated complex cepstra. These signals generally have more advanced singularities than the poles of signals with rational z-transforms. Examples are presented which illustrate the behavior of signals having branch points and essential singularities.     

Extraction of fetal electrocardiogram using adaptive neuro-fuzzy inference systems

In this paper, we investigate the use of adaptive neuro-fuzzy inference systems (ANFIS) for fetal electrocardiogram (FECG) extraction from two ECG signals recorded at the thoracic and abdominal areas of the mother's skin. The thoracic ECG is assumed to be almost completely maternal (MECG) while the abdominal ECG is considered to be composite as it contains both the mother's and the fetus' ECG signals. The maternal component in the abdominal ECG signal is a nonlinearly transformed version of the MECG. We use an ANFIS network to identify this nonlinear relationship, and to align the MECG signal with the maternal component in the abdominal ECG signal. Thus, we extract the FECG component by subtracting the aligned version of the MECG signal from the abdominal ECG signal. We validate our technique on both real and synthetic ECG signals. Our results demonstrate the effectiveness of the proposed technique in extracting the FECG component from abdominal signals of very low maternal to fetal signal-to-noise ratios. The results also show that the technique is capable of extracting the FECG even when it is totally embedded within the maternal QRS complex.     

一类基于非线性PCA准则的复数信号盲分离算法

在阵列信号处理过程中，经常遇到复数信号盲分离问题。例如，卷积混合型的源信号的盲分离；声纳信号盲分离。本文提出了一类基于非线性准则的复数信号盲分离算法。将非线性函数引入学习过程，由算法自动调节学习速率。计算机仿真实验验证了算法的有效性，文中给出了验证结果。     

线性调频与相位编码混合雷达信号处理仿真

为了保证雷达系统能够在复杂的电磁环境中有效地工作,雷达信号的选择尤为重要。本文采用线性调频信号与相位编码信号相结合的码内线性调频信号作为雷达信号,针对这个信号进行了整个雷达信号处理的仿真。仿真结果表明,码内线性调频信号具有较好的抗干扰的特性。     

Analog-to-digital conversion. part 5

In part 4 of the series (Schmalzel and Rauth, 2005), the signal conditioning stage for a variety of transducer types and sensors was discussed. The output of this stage in the measurement chain is typically an analog signal that can drive an actuator or display or be converted into digital form. Since the advent of monolithic analog/digital converters (ADCs) in the 1970s, digital measurement systems have become the standard. Today, almost all signal processing takes place in the digital domain where signals can be flexibly manipulated in complex ways when compared to their analog counterparts. Before we can enter the Utopian realm of digital signal processing, analog signals need to be converted into digital form, which is the subject of this tutorial.     

Nonlinear PSK and combined nonlinear PSK/FSK modulation

Two classes of constant envelope signals called, nonlinear PSK and combined nonlinear PSK/FSK are introduced. Nonlinear PSK signals select a constant phase angle during each interval depending on the state of the signal and the transmitted symbol. Combined nonlinear PSK/FSK signals select a linear phase variation during each interval and a discrete phase variation at the end of each interval depending on the current state and the transmitted symbol. Both classes of signals achieve the highest constraint length allowed by the number of states. The numerical results presented at preselected numbers of states show that these signals produce significantly high minimum distances. Distances higher than those found in the literature at the same number of states are reported. The spectra of nonlinear PSK signals are almost identical to the spectrum of BPSK signals, while those of combined nonlinear PSK/FSK signals are continuous but similar to that of BPSK signals     

基于半实物仿真的复杂信号生成设计

针对卫星导航系统干扰模拟与抗干扰测试需求,基于半实物仿真原理,提出了一种利用ADS软件和矢量信号发生器产生自定义波形复杂信号的方法。对半实物仿真系统的硬件平台的搭建要点进行了介绍,完成了复杂信号在ADS系统平台下的建模与仿真,阐述了半实物仿真流程。利用矢量信号分析仪89600S对生成的复杂信号进行了测试,并通过与ADS仿真结果的对比分析,验证该方法的可行性。     

Reconstruction of Complex Sparse Signals in Compressed Sensing with Real Sensing Matrices

The existing greedy algorithms for the reconstruction in compressed sensing were designed no matter which type the original sparse signals and sensing matrices have, real or complex. The reconstruction algorithms definitely apply to real sensing matrices and complex sparse signals, but they are not customized to this situation so that we could improve those algorithms further. In this paper, we elaborate on the compressed sensing with real sensing matrices when the original sparse signals are complex. We propose two reconstruction algorithms by modifying the orthogonal matching pursuit to include some procedures specialized to this setting. It is shown via analysis and simulation that the proposed algorithms have better reconstruction success probability than conventional reconstruction algorithms.