The design and development of an undergraduate signal processing laboratory

The School of Electrical and Electronic Systems Engineering of Queensland University of Technology (like many other universities around the world) has recognised the importance of complementing the teaching of signal processing with computer based experiments. A laboratory has been developed to provide a "hands-on" approach to the teaching of signal processing techniques. The motivation for the development of this laboratory was the cliche "What I hear I remember but what I do I understand." The laboratory has been named as the "Signal Computing and Real-time DSP Laboratory" and provides practical training to approximately 150 final year undergraduate students each year. The paper describes the novel features of the laboratory, techniques used in the laboratory based teaching, interesting aspects of the experiments that have been developed and student evaluation of the teaching techniques

A Sub-Nyquist Sampling Method For Computing The Level-crossing-times Of An Analog Signal: Theory And Applications

We address the problem of computing the level-crossings of an analog signal from samples measured on a uniform grid. Such a problem is important, for example, in multilevel analog-to-digital (A/D) converters. The first operation in such sampling modalities is a comparator, which gives rise to a bilevel waveform. Since bilevel signals are not bandlimited, measuring the level-crossing times exactly becomes impractical within the conventional framework of Shannon sampling. In this paper, we propose a novel sub-Nyquist sampling technique for making measurements on a uniform grid and thereby for exactly computing the level-crossing times from those samples. The computational complexity of the technique is low and comprises simple arithmetic operations. We also present a finite-rate-of-innovation sampling perspective of the proposed approach and also show how exponential splines fit in naturally into the proposed sampling framework. We also discuss some concrete practical applications of the sampling technique.

Optimized strategy for integrated traffic and transit signal control

This paper proposes a unique and innovative approach to integrate transit signal priority control into a traffic adaptive signal control strategy. The proposed strategy was named OSTRAC (Optimized Strategy for integrated TRAffic and TRAnsit signal Control). The cornerstones of OSTRAC include an online microscopic traffic f low prediction model and a Genetic Algorithm (GA) based traffic signal timing module. A sensitivity analysis was conducted to determine the critical GA parameters. The developed traffic f low model demonstrated reliable prediction results through a test. OSTRAC was evaluated by comparing its performance to three other signal control strategies. The evaluation results revealed that OSTRAC efficiently and effectively reduced delay time of general traffic and also transit vehicles.

Estudo da precisão e da exatidão da técnica da birrefringência acústica na avaliação de tensões residuais e aplicadas.

Este trabalho apresenta um procedimento numérico para o estudo da precisão e da exatidão da técnica de birrefringência acústica como usada no Instituto de Engenharia Nuclear (IEN) para avaliação de tensões residuais e aplicadas em estruturas metálicas. Esse procedimento deverá ser incorporado posteriormente ao módulo de processamento de sinal do sistema ultrassônico utilizado no Laboratório de Ultrassom do IEN para levar em conta, de forma automática e sistemática, as incertezas nos dados de entrada e as suas propagações ao longo dos cálculos efetuados. A birrefringência acústica é geralmente definida a partir das velocidades de duas ondas ultrassônicas volumétricas de incidência normal e ortogonais entre si. A birrefringência pode ser definida diretamente a partir dos tempos de percurso dessas duas ondas, uma vez que elas percorrem o mesmo espaço físico. Os tempos de percurso das ondas podem ser assim considerados como as variáveis primárias de interesse. Por meio da teoria da acustoelasticidade é possível relacionar a birrefringência acústica com as tensões atuantes no material explorando o fato da velocidade da onda ultrassônica ser afetada pela presença de um campo de tensões. Nesta dissertação elaborou-se um conjunto de planilhas eletrônicas no aplicativo Microsoft Excel para efetuar de forma automática todos os cálculos necessários ao objetivo proposto, levando em conta as incertezas nos dados, sua propagação ao longo dos cálculos e o número de dígitos significativos nos resultados. Como exemplo do procedimento desenvolvido, o estudo da precisão e da exatidão na determinação das tensões em uma viga de aço sob flexão pela técnica da birrefringência acústica é apresentado. Como valor de referência, para fins do cálculo da exatidão alcançada, utilizou-se uma solução analítica derivada da teoria clássica da resistência de materiais. Os resultados encontrados indicaram uma razoável precisão, com um erro relativo menor do que 8%, e uma baixa exatidão, menor do que 57%, nos pontos da viga sujeitos às maiores tensões principais de flexão.

Dynamic and isometric protocols of knee extension: Effect of fatigue on the EMG signal

The objective of this study was to analyze the electromyographic (EMG) signal behavior of rectus femoris (RF), vastus medialis (VM), vastus lateralis (VL) and biceps femoris (caput longum) (BFCL) from nine women during fatiguing dynamic and isometric knee extensions tests and to determine their EMGFT (Electromyographic Fatigue Threshold). Surface electrodes, biological signal acquisition module, analogical-digital converter board and specific software were used. The RMS (Root Mean Square) values obtained from concentric phase (80 to 30 degrees) of the dynamic knee extension andfrom isometric contraction were correlated with time on each load by linear regression analysis. The respective slopes were correlated with the correspondent load to determine the EMGFT. Force (Kgf) and median frequency - MF (Hz) obtained during MIVC (Maximal Isometric Voluntary Contraction) performed before and after the fatiguing tests were calculated in Matlab environment. The results demonstrated that the endurance time decreases with higher loads the EMG amplitude increase with time and was greater at higher loads, between muscles in dynamic exercise the RF and VL showed higher slopes, and in isometric exercise the VL showed the same behavior The EMGFT values were similar in both exercises; the force values predominantly decreased after fatiguing tests; however the MF only decreased after some loads. The protocols proposed allowed standardizing protocols at least to induce the fatigue process and to determine the EMGFT as an endurance indicative, which may be used to evaluate the effectiveness of rehabilitative or training interventions indicated to reduce muscle weakness and fatigue.

Waves, analytical signals, and some postulates of quantum theory

In this paper we apply the formalism of the analytical signal theory to the Schrödinger wavefunction. Making use exclusively of the wave-particle duality and the rinciple of relativistic covariance, we actually derive the form of the quantum energy and momentum operators for a single nonrelativistic particle. Without using any more quantum postulates, and employing the formalism of the characteristic function, we also derive the quantum-mechanical prescription for the measurement probability in such cases.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

GDNF Receptors: Veterans and Novices

Neurotrophic factors play essential role in the development and functioning of the nervous system and other organs. Glial cell line-Derived Neurotrophic Factor (GDNF) family ligands (GFLs) are of particular interest because they promote the survival of dopaminergic neurons in vitro, in Parkinson s disease animal models and in patients. GDNF is also a potent survival factor for the central motoneurons and thus is considered as a potential lead for the treatment of amyotrophic lateral sclerosis. The survival promoting receptor complex for GFLs consists of a ligand-specific co-receptor, GFRα and a signal transducing module, receptor tyrosine kinase RET. At least GDNF and persephin, a GFL, have established functions outside central nervous system. GDNF is crucial for enteric nervous system and kidney development as well as for spermatogenesis. Persephin controls calcitonin secretion. Communication between cells often occurs in the extracellular matrix (ECM), a meshwork, which is secreted and deposited by the cells and is mainly composed of fibrillar proteins and polymerized sugars. We evaluated the relationship between GFLs and extracellular matrix components and demonstrated that three GFLs - GDNF, neurturin and artemin bind heparan sulfates with nanomolar affinities. The fourth member of the family - persephin binds these polysaccharides thousand times less tightly. GDNF, neurturin and artemin also bind with high affinity to heparan sulfate proteoglycan (HSPG) isolated from the nervous system, syndecan-3. GDNF signals through HSPGs, evoking Src family kinase activation. This signaling induces cell spreading, hippocampal neurite outgrowth in vitro and cellular migration. Specifically, GDNF signaling through syndecan-3 is important for embryonic cortical neuron migration. Syndecan-3-deficient mice, similarly to mice lacking GDNF, have less GABAergic neurons in their cortex, as compared to the wild-type mice. This fact provides indirect evidence that GDNF interaction with syndecan-3 is important for cortical brain development. Noteworthy, in non-neuronal tissues GFLs may signal via other syndecans. We also present the structural model for a GDNF co-receptor, GFRα1. The X-ray structure of the GFRα1 domain 3 was solved with 1.8 Å resolution, revealing a new protein fold. Later we also solved the structure of the truncated GFRα1 in the complex with GDNF and this model was confirmed by site-directed mutagenesis. In summary, our work contributed to the structural characterization of GFRα-based receptor complex and revealed a new receptor for GDNF, neurturin and artemin the HSPG syndecan-3. This information is critically important for the development of GFRα/RET agonists for the treatment of neurodegenerative diseases.

Magnetic field and pressure effects in a saturated gas laser amplifier

Theoretical and experimental studies of a gas laser amplifier are presented, assuming the amplifier is operating with a saturating optical frequency signal. The analysis is primarily concerned with the effects of the gas pressure and the presence of an axial magnetic field on the characteristics of the amplifying medium. Semiclassical radiation theory is used, along with a density matrix description of the atomic medium which relates the motion of single atoms to the macroscopic observables. A two-level description of the atom, using phenomenological source rates and decay rates, forms the basis of our analysis of the gas laser medium. Pressure effects are taken into account to a large extent through suitable choices of decay rate parameters.

Two methods for calculating the induced polarization of the atomic medium are used. The first method utilizes a perturbation expansion which is valid for signal intensities which barely reach saturation strength, and it is quite general in applicability. The second method is valid for arbitrarily strong signals, but it yields tractable solutions only for zero magnetic field or for axial magnetic fields large enough such that the Zeeman splitting is much larger than the power broadened homogeneous linewidth of the laser transition. The effects of pressure broadening of the homogeneous spectral linewidth are included in both the weak-signal and strong-signal theories; however the effects of Zeeman sublevel-mixing collisions are taken into account only in the weak-signal theory.

The behavior of a He-Ne gas laser amplifier in the presence of an axial magnetic field has been studied experimentally by measuring gain and Faraday rotation of linearly polarized resonant laser signals for various values of input signal intensity, and by measuring nonlinearity - induced anisotropy for elliptically polarized resonant laser signals of various input intensities. Two high-gain transitions in the 3.39-μ region were used for study: a J = 1 to J = 2 (3s₂ → 3p₄) transition and a J = 1 to J = 1 (3s₂ → 3p₂) transition. The input signals were tuned to the centers of their respective resonant gain lines.

The experimental results agree quite well with corresponding theoretical expressions which have been developed to include the nonlinear effects of saturation strength signals. The experimental results clearly show saturation of Faraday rotation, and for the J = 1 t o J = 1 transition a Faraday rotation reversal and a traveling wave gain dip are seen for small values of axial magnetic field. The nonlinearity induced anisotropy shows a marked dependence on the gas pressure in the amplifier tube for the J = 1 to J = 2 transition; this dependence agrees with the predictions of the general perturbational or weak signal theory when allowances are made for the effects of Zeeman sublevel-mixing collisions. The results provide a method for measuring the upper (neon 3s₂) level quadrupole moment decay rate, the dipole moment decay rates for the 3s₂ → 3p₄ and 3s₂ → 3p₂ transitions, and the effects of various types of collision processes on these decay rates.

基于网络化虚拟仪器的机器人传感器实验平台

设计了基于网络化虚拟仪器的多节点机器人传感器实验平台系统,利用COM、软件插件等技术开发了虚拟控件和信号处理软件模块,用户可通过PPL创建自定义的信号处理模块,为进行面向智能机器人控制的传感器测试、标定、组网等奠定了基础。

东海陆架盆地复杂天然气藏地震勘探判别技术研究

Exploration study proves that East sea shelf basin embeds abundant hydrocarbon resources. However, the exploration knowledge of this area is very low. Many problems in exploration are encountered here. One of them is that the gas reservoir of this area, with rapid lateral variation, is deeply buried. Correlation of Impendence between sandstone, gas sand and shale is very poor. Another problem is that the S/N ratio of the seismic data is very low and multiples are relatively productive which seriously affect reservoir identification. Resolution of the seismic data reflected from 2500-3000 meter is rather low, which seriously affects the application of hydrocarbon direct identification (HDI) technology. This research established a fine geological & geophysical model based on drilling、well logging、geology&seismic data of East sea Lishui area. A Q value extraction method from seismic data is proposed. With this method, Q value inversion from VSP data and seismic data is performed to determine the subsurface absorption of this area. Then wave propagation and absorption rule are in control. Field acquisition design can be directed. And at the same time, with the optimization of source system, the performance of high resolution seismic acquisition layout system is enhanced. So the firm foundation is ensured for east sea gas reservoir exploration. For solving the multiple and amplitude preserving problems during the seismic data processing, wave equation pre-stack amplitude preservation migration and wave equation feedback iteratively multiple attenuation technologies are developed. Amplitude preservation migration technology can preserve the amplitude of imaging condition and wave-field extrapolation. Multiple removing technology is independent of seismic source wavelet and velocity model, which avoiding the weakness of Delft method. Aiming at the complicated formation condition of the gas reservoir in this area, with dissecting typical hydrocarbon reservoir, a series of pertinent advanced gas reservoir seismic identification technologies such as petrophysical properties analyzing and seismic modeling technology、pre-stack/post-stack joint elastic inversion, attribute extraction technology based on seismic non-stationary signal theory and formation absorption characteristic and so on are studied and developed. Integrated analysis of pre-stack/post-stack seismic data, reservoir information, rock physics and attribute information is performed. And finally, a suit of gas reservoir identification technology is built, according to the geological and geophysical characteristics of this area. With developed innovative technologies, practical application and intergrated interpretation appraisal researches are carried out in Lishui 36-1.The validity of these technologies is tested and verified. Also the hydrocarbon charging possibility and position of those three east sea gas exploration targets are clearly pointed out.

Text-dependent speaker recognition using the Fuzzy ARTMAP neural network

Speaker recognition is the process of automatically recognizing the speaker by analyzing individual information contained in the speech waves. In this paper, we discuss the development of an intelligent system for text-dependent speaker recognition. The system comprises two main modules, a wavelet-based signal-processing module for feature extraction of speech waves, and an artificial-neural-network-based classifier module to identify and categorize the speakers. Wavelet is used in de-noising and in compressing the speech signals. The wavelet family that we used is the Daubechies Wavelets. After extracting the necessary features from the speech waves, the features were then fed to a neural-network-based classifier to identify the speakers. We have implemented the Fuzzy ARTMAP (FAM) network in the classifier module to categorize the de-noised and compressed signals. The proposed intelligent learning system has been applied to a case study of text-dependent speaker recognition problem.

On the reliability of visual communication in vertebrate-dispersed fruits

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)