Detecting finite bandwidth periodic signals in stationary noise using the signal coherence spectrum

All signals that appear to be periodic have some sort of variability from period to period regardless of how stable they appear to be in a data plot. A true sinusoidal time series is a deterministic function of time that never changes and thus has zero bandwidth around the sinusoid's frequency. A zero bandwidth is impossible in nature since all signals have some intrinsic variability over time. Deterministic sinusoids are used to model cycles as a mathematical convenience. Hinich [IEEE J. Oceanic Eng. 25 (2) (2000) 256-261] introduced a parametric statistical model, called the randomly modulated periodicity (RMP) that allows one to capture the intrinsic variability of a cycle. As with a deterministic periodic signal the RMP can have a number of harmonics. The likelihood ratio test for this model when the amplitudes and phases are known is given in [M.J. Hinich, Signal Processing 83 (2003) 1349-13521. A method for detecting a RMP whose amplitudes and phases are unknown random process plus a stationary noise process is addressed in this paper. The only assumption on the additive noise is that it has finite dependence and finite moments. Using simulations based on a simple RMP model we show a case where the new method can detect the signal when the signal is not detectable in a standard waterfall spectrograrn display. (c) 2005 Elsevier B.V. All rights reserved.

Femtosecond Rotational Raman Coherence Spectroscopy of Cyclohexane in a Pulsed Supersonic Jet

We combine the technique of femtosecond degenerate four-wave mixing (fs-DFWM) with a high repetition-rate pulsed supersonic jet source to obtain the rotational coherence spectrum (RCS) of cold cyclohexane (C(6)H(12)) with high signal/noise ratio. In the jet expansion, the near-parallel flow pattern combined with rapid translational cooling effectively eliminate dephasing collisions, giving near-constant RCS signal intensities over time delays up to 5 ns. The vibrational cooling in the jet eliminates the thermally populated vibrations that complicate the RCS coherences of cyclohexane at room temperature [Bragger, G.; et al. J. Phys. Chem. A 2011, 115, 9567]. The rotational cooling reduces the high-J rotational-state population, yielding the most accurate ground-state rotational constant to date, B(0) = 4305.859(9) MHz. Based on this B(0), a reanalysis of previous room-temperature gas-cell RCS measurements of cydohexane gives improved vibration rotation interaction constants for the v(32), v(6), v(16), and v(24) vibrational states. Combining the experimental B(0)(C(6)H(12)) with CCSD(T) calculations yields a very accurate semiexperimental equilibrium structure of the chair isomer of cyclohexane

Spectrum sensing, detection and optimisation in cognitive radio for non-stationary primary user signals

Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

Development of a method fon non-destructive testing of fruits using scanning laser vibrometry (SLV)

Quality control on fruits requires reliable methods, able to assess with reasonable accuracy and possibly in a non-destructive way their physical and chemical characteristics. More specifically, a decreased firmness indicates the presence of damage or defects in the fruit or else that the fruit has exceeded its “best before date”, becoming unsuitable for consumption. In high-value exotic fruits, such as mangoes, where firmness cannot be easily measured from a simple observation of texture, colour changes and unevenness of fruits surface, the use of non-destructive techniques is highly recommendable. In particular, the application of Laser vibrometry, based on the Doppler effect, a non-contact technique sensitive to differences in displacements inferior to the nanometre, appears ideal for a possible on-line control on food. Previous results indicated that a phase shift can be in a repeatable way associated with the presence of damage on the fruit, whilst a decreased firmness results in significant differences in the displacement of the fruits under the same excitation signal. In this work, frequency ranges for quality control via the application of a sound chirp are suggested, based on the measurement of the signal coherence. The variations of the average vibration spectrum of a grid of points, or of point-by-point signal velocity allows the go-no go recognition of “firm” and “over-ripe” fruits, with notable success in the particular case of mangoes. The future exploitation of this work will include the application of this method to allow on-line control during conveyor belt distribution of fruits.

The role of cardiopulmonary signals in the dynamics of the eye's wavefront aberrations

Abstract—The role of cardiopulmonary signals in the dynamics of wavefront aberrations in the eye has been examined. Synchronous measurement of the eye’s wavefront aberrations, cardiac function, blood pulse, and respiration signals were taken for a group of young, healthy subjects. Two focusing stimuli, three breathing patterns, as well as natural and cycloplegic eye conditions were examined. A set of tools, including time–frequency coherence and its metrics, has been proposed to acquire a detailed picture of the interactions of the cardiopulmonary system with the eye’s wavefront aberrations. The results showed that the coherence of the blood pulse and its harmonics with the eye’s aberrations was, on average, weak (0.4 ± 0.15), while the coherence of the respiration signal with eye’s aberrations was, on average, moderate (0.53 ± 0.14). It was also revealed that there were significant intervals during which high coherence occurred. On average, the coherence was high (>0.75) during 16% of the recorded time, for the blood pulse, and 34% of the time for the respiration signal. A statistically significant decrease in average coherence was noted for the eye’s aberrations with respiration in the case of fast controlled breathing (0.5 Hz). The coherence between the blood pulse and the defocus was significantly larger for the far target than for the near target condition. After cycloplegia, the coherence of defocus with the blood pulse significantly decreased, while this was not the case for the other aberrations. There was also a noticeable, but not statistically significant, increase in the coherence of the comatic term and respiration in that case. By using nonstationary measures of signal coherence, a more detailed picture of interactions between the cardiopulmonary signals and eye’s wavefront aberrations has emerged.

频谱泄漏对正弦相位调制干涉测量精度的影响何

在正弦相位调制(SPM)干涉仪中,若调制频率或者采样频率发生变化将使干涉信号出现频谱泄漏,减小了谐波分量的幅值,在测量结果中引入了误差。对频谱泄漏的产生及其对测量精度的影响进行了理论分析,获得了频谱泄漏引入测量误差的计算方法。实验测得频率漂移量在-0.3～0.3 Hz内,得到的频谱泄漏引入的误差为0.3～7.9 nm,当超出这个范围时,频谱泄漏误差将迅速增长。实验结果与模拟分析结果一致。

Detecting intraday periodicities with application to high frequency exchange rates

Many recent papers have documented periodicities in returns, return volatility, bid–ask spreads and trading volume, in both equity and foreign exchange markets. We propose and employ a new test for detecting subtle periodicities in time series data based on a signal coherence function. The technique is applied to a set of seven half-hourly exchange rate series. Overall, we find the signal coherence to be maximal at the 8-h and 12-h frequencies. Retaining only the most coherent frequencies for each series, we implement a trading rule that is based on these observed periodicities. Our results demonstrate in all cases except one that, in gross terms, the rules can generate returns that are considerably greater than those of a buy-and-hold strategy, although they cannot retain their profitability net of transactions costs. We conjecture that this methodology could constitute an important tool for financial market researchers which will enable them to detect, quantify and rank the various periodic components in financial data better.

Sistema para realização de medidas de luminescência com excitação por raios X

In this work is presented a versatile system for X-ray excited optical luminescence (XEOL) measurements. The apparatus was assembled from a sample holder connected to an optical fiber responsibly for the acquisition of the scintillation signal. The spectrum is registered with a CCD coupled in a spectrograph provided with diffraction gratings. The system performance was analyzed by exciting GdAlO3:Eu3+ 3.0 at.% with X-rays from a diffractometer and measuring the emission spectra. The system can be used to obtain precise and reliable spectroscopic properties of samples with various conformations without the loss of the required safety when dealing with ionizing radiations.

Cupiennin 1a, an antimicrobial peptide from the venom of the neotropical wandering spider Cupiennius salei, also inhibits the formation of nitric oxide by neuronal nitric oxide synthase

Cupiennin 1a (GFGALFKFLAKKVAKTVAKQAAKQGAKYVVNKQME-NH2) is a potent venom component of the spider Cupiennius salei. Cupiennin 1a shows multifaceted activity. In addition to known antimicrobial and cytolytic properties, cupiennin 1a inhibits the formation of nitric oxide by neuronal nitric oxide synthase at an IC50 concentration of 1.3 +/- 0.3 microM. This is the first report of neuronal nitric oxide synthase inhibition by a component of a spider venom. The mechanism by which cupiennin 1a inhibits neuronal nitric oxide synthase involves complexation with the regulatory protein calcium calmodulin. This is demonstrated by chemical shift changes that occur in the heteronuclear single quantum coherence spectrum of 15N-labelled calcium calmodulin upon addition of cupiennin 1a. The NMR data indicate strong binding within a complex of 1 : 1 stoichiometry.

Demonstration of nonlinear inverse synthesis transmission over transoceanic distances

Nonlinear Fourier transform (NFT) and eigenvalue communication with the use of nonlinear signal spectrum (both discrete and continuous), have been recently discussed as promising transmission methods to combat fiber nonlinearity impairments. In this paper, for the first time, we demonstrate the generation, detection and transmission performance over transoceanic distances of 10 Gbaud and nonlinear inverse synthesis (NIS) based signal (4 Gb/s line rate), in which the transmitted information is encoded directly onto the continuous part of the signal nonlinear spectrum. By applying effective digital signal processing techniques, a reach of 7344 km was achieved with a bit-error-rate (BER) (2.1×10-2) below the 20% FEC threshold. This represents an improvement by a factor of ~12 in data capacity x distance product compared with other previously demonstrated NFT-based systems, showing a significant advance in the active research area of NFT-based communication systems.

Swath bathymetry using phase difference: Theoretical analysis of acoustical measurement precision

The phase difference principle is widely applied nowadays to sonar systems used for sea floor bathymetry, The apparent angle of a target point is obtained from the phase difference measured between two close receiving arrays. Here we study the influence of the phase difference estimation errors caused by the physical structure of the backscattered signals. It is shown that, under certain current conditions, beyond the commonly considered effects of additive external noise and baseline decorrelation, the processing may be affected by the shifting footprint effect: this is due to the fact that the two interferometer receivers get simultaneous echo contributions coming from slightly shifted seabed parts, which results in a degradation of the signal coherence and, hence, of the phase difference measurement. This geometrical effect is described analytically and checked with numerical simulations, both for square- and sine-shaped signal envelopes. Its relative influence depends on the geometrical configuration and receiver spacing; it may be prevalent in practical cases associated with bathymetric sonars. The cases of square and smooth signal envelopes are both considered. The measurements close to nadir, which are known to be especially difficult with interferometry systems, are addressed in particular.

Estimation of vibration amplitude in Fourier domain optical coherence tomography interferometric signals from Doppler spectrum

In presented method combination of Fourier and Time domain detection enables to broaden the effective bandwidth for time dependent Doppler Signal that allows for using higher-order Bessel functions to calculate unambiguously the vibration amplitudes.

Spectrum sensing optimisation for dynamic primary user signal

We propose a multi-layer spectrum sensing optimisation algorithm to maximise sensing efficiency by computing the optimal sensing and transmission durations for a fast changing, dynamic primary user. Dynamic primary user traffic is modelled as a random process, where the primary user changes states during both the sensing period and transmission period to reflect a more realistic scenario. Furthermore, we formulate joint constraints to correctly reflect interference to the primary user and lost opportunity of the secondary user during the transmission period. Finally, we implement a novel duty cycle based detector that is optimised with respect to PU traffic to accurately detect primary user activity during the sensing period. Simulation results show that unlike currently used detection models, the proposed algorithm can jointly optimise the sensing and transmission durations to simultaneously satisfy the optimisation constraints for the considered primary user traffic.

Optimal sparsifying bases for frequency-domain optical-coherence tomography

We address the reconstruction problem in frequency-domain optical-coherence tomography (FDOCT) from under-sampled measurements within the framework of compressed sensing (CS). Specifically, we propose optimal sparsifying bases for accurate reconstruction by analyzing the backscattered signal model. Although one might expect Fourier bases to be optimal for the FDOCT reconstruction problem, it turns out that the optimal sparsifying bases are windowed cosine functions where the window is the magnitude spectrum of the laser source. Further, the windowed cosine bases can be phase locked, which allows one to obtain higher accuracy in reconstruction. We present experimental validations on real data. The findings reported in this Letter are useful for optimal dictionary design within the framework of CS-FDOCT. (C) 2012 Optical Society of America

AN ITERATIVE ALGORITHM FOR PHASE RETRIEVAL WITH SPARSITY CONSTRAINTS: APPLICATION TO FREQUENCY DOMAIN OPTICAL COHERENCE TOMOGRAPHY

We address the problem of phase retrieval, which is frequently encountered in optical imaging. The measured quantity is the magnitude of the Fourier spectrum of a function (in optics, the function is also referred to as an object). The goal is to recover the object based on the magnitude measurements. In doing so, the standard assumptions are that the object is compactly supported and positive. In this paper, we consider objects that admit a sparse representation in some orthonormal basis. We develop a variant of the Fienup algorithm to incorporate the condition of sparsity and to successively estimate and refine the phase starting from the magnitude measurements. We show that the proposed iterative algorithm possesses Cauchy convergence properties. As far as the modality is concerned, we work with measurements obtained using a frequency-domain optical-coherence tomography experimental setup. The experimental results on real measured data show that the proposed technique exhibits good reconstruction performance even with fewer coefficients taken into account for reconstruction. It also suppresses the autocorrelation artifacts to a significant extent since it estimates the phase accurately.