Spatial filtering and neocortical dynamics: estimates of EEGcoherence

The spatial statistics of scalp electroencephalogram (EEG) are usually presented as coherence in individual frequency bands. These coherences result both from correlations among neocortical sources and volume conduction through the tissues of the head. The scalp EEG is spatially low-pass filtered by the poorly conducting skull, introducing artificial correlation between the electrodes. A four concentric spheres (brain, CSF, skull, and scalp) model of the head and stochastic field theory are used here to derive an analytic estimate of the coherence at scalp electrodes due to volume conduction of uncorrelated source activity, predicting that electrodes within 10-12 cm can appear correlated. The surface Laplacian estimate of cortical surface potentials spatially bandpass filters the scalp potentials reducing this artificial coherence due to volume conduction. Examination of EEG data confirms that the coherence estimates from raw scalp potentials and Laplacians are sensitive to different spatial bandwidths and should be used in parallel in studies of neocortical dynamic function     

Estimating random amplitude polynomial phase signals: acyclostationary approach

Modeling of a class of nonstationary signals with randomly time-varying amplitude and parametric polynomial phase is addressed. A novel approach is proposed for the estimation of the time-varying phase by exploiting the higher order cyclostationarity of these signals. The method does not require nonlinear search, is easy to implement, and yields consistent estimates for the parameters. The resulting algorithms are theoretically tolerant to a large class of noises including additive stationary non-Gaussian noise and any Gaussian noise. Simulation examples supporting the theory are provided     

一种减少频谱泄露的幅值和相位自校正算法

频谱泄露是影响谐波检测和频谱分析的重要原因,而采样频率与信号频率不同步是造成频谱泄露的根本原因。现提出一种幅值和相位自校正的算法,可通过自动校正减小异步采样时DFT产生的幅值和相位的误差,降低频谱泄露造成的影响,对同步采样条件下的DFT没有影响,并给出算法的实现步骤和仿真结果,证明了该算法能精确地得到信号的实际幅值和相位,对于采样点数较少的信号也能给出较高的测量精度,而且该算法具有迭代特性,原理简单,是频谱分析中的一种有效方法。     

Coded noncoherent communication with amplitude/phase modulation: from shannon theory to practical architectures

We develop bandwidth efficient radio transceivers, using amplitude/phase modulations, for frequency non-selective channels whose time variations are typical of outdoor mobile wireless systems. The transceiver is noncoherent, neither requiring pilots for channel estimation and tracking nor assuming prior channel knowledge on the part of the receiver. Serial concatenation of a binary outer channel code with an inner differential modulation code provides a turbo structure that, along with the channel memory, is exploited for joint iterative channel and data estimation. While prior work on noncoherent communication mainly focuses on PSK alphabets, we consider a moderate to high SNR regime in which amplitude/phase constellations are more efficient. First, the complexity of block noncoherent demodulation is reduced to a level that is comparable to coherent receivers. Then, a tool for choosing the constellation and bit-to-symbol mapping is developed by adapting Extrinsic Information Transfer (EXIT) charts for noncoherent demodulation. The recommended constellations differ significantly from standard coherent channel constellations, and from prior recommendations for uncoded noncoherent systems. The analysis shows that standard convolutional codes are nearly optimal when paired with differential amplitude/phase modulation.     

Array grating lobes due to periodic phase, amplitude, and time delay quantization

Simple approximate formulas and generalized curves to evaluate the grating lobe levels of various kinds of contiguous subarrays with uniform illumination within each subarray are presented. The cases considered include phase quantization due to discrete phase shifters, amplitude taper at subarray input ports and time delay at the subarray input ports. In addition, the work is generalized to include certain cases of quantized phase or time delay at the input ports in addition to amplitude taper at subarray input ports.     

Spectral baseline ripple in hot-electron bolometer mixers due to local oscillator phase and amplitude instabilities

High resolution millimetre and submillimetre wave astronomical spectrometers using hot-electron bolometer mixers as detectors often show marked “standing wave patterns” in the spectral baseline. LO phase noise contributes through two mechanisms: the phase noise side-bands may be converted to amplitude noise in the source because of the power-frequency characteristic of the source, or they can be converted to in-band amplitude noise through the action of the quasi-optical discriminator formed by the mixer, beam-splitter and telescope structure. The baseline ripple components due to each of these mechanisms have different characteristic periods, and under some circumstances can dominate the spectrometer baseline. The ripple levels estimated using the theory agree well with those observed in practice. It is shown that with careful design systematic effects due to this cause can be reduced to a negligible level.     

Analysis of the behaviours of phase and amplitude mismatch compensators to achieve 82.5 dB image rejection ratio

This article presents an experiment to analyse the behaviour of phase and amplitude mismatch compensators in quadrature receivers. The experiment shows that the input signal level and convergence time affect image rejection ratio (IRR) and signal to noise and distortion ration (SNDR). Based on the findings, design guidelines are suggested and an exceptionally high 82.5 dB IRR is demonstrated in a digital low intermediate frequency (low-IF) Weaver receiver constructed using off-the-shelf components, whereas existing mismatch compensation techniques can only achieve 50 to 65 dB IRR.     

Wavelet-based Bayesian image estimation: from marginal and bivariate prior models to multivariate prior models.

Prior models play an important role in the wavelet-based Bayesian image estimation problem. Although it is well known that a residual dependency structure always remains among natural image wavelet coefficients, only few multivariate prior models with a closed parametric form are available in the literature. In this paper, we develop new multivariate prior models that not only match well with the observed statistics of the wavelet coefficients of natural images, but also have a simple parametric form. These prior models are very effective for Bayesian image estimation and lead to an improved estimation performance over related earlier techniques.     

DIFFERENTIAL AMPLITUDE PHASE SHIFT KEYING：A NEW MODULATION METHOD FOR TURBO CODE IN DIGITAL RADIO BROADCASTING

The multilevel modulation techniques of M-Differential Amplitude Phase Shift Keying(DAPSK)have been proposed in combination with Turbo code scheme for digital radio broad-casting bands below 30 MHz radio channel.Comparison of this modulation method with channel coding in an Additive White Gaussian Noise(AWGN)and mulit-path fading channels has been presented.The analysis provides an iterative decoding of the Turbo code.     

Low and midrange modulation frequency response for YBCO infrareddetectors: interface effects on the amplitude and phase

Bolometers were designed and fabricated from YBa₂Cu₃O_7-x films on MgO, SrTiO₃ , and LaAlO₃ substrates. Both the magnitude and phase of the IR-response of the detectors were investigated from 0.5 Hz to 100 kHz modulation frequencies, and from 0.8 to 20 micron wavelengths. Effects of the film-substrate thermal boundary resistance, R_bd, and the substrate-cold head thermal boundary resistance, R_s-c, were investigated. The effect of R_bd is shown to be significant in the response only at high frequencies, above 100 kHz. The response at low frequencies is found to be determined by R _s-c up to “knee” frequencies of 15, 60, and 600 Hz, for 0.05-cm thick SrTiO₃, LaAlO₃, and MgO substrates, respectively. A model for the bolometric response is developed, that correctly predicts the “knee” frequencies and the measured phase and amplitude of the response versus frequency up to about 10 kHz, including the predicted change from a f^-1 to a f^-1/2 dependence at the “knee” frequency. At the low bias currents used to operate the bolometers, Joule heating effects are negligible. From the model and experimental data, a specific heat of 0.59 J/K·cm³ has been deduced for LaAlO₃ at T≈90 K     

Dynamical resetting of the human brain at epileptic seizures: application of nonlinear dynamics and global optimization techniques

Epileptic seizures occur intermittently as a result of complex dynamical interactions among many regions of the brain. By applying signal processing techniques from the theory of nonlinear dynamics and global optimization to the analysis of long-term (3.6 to 12 days) continuous multichannel electroencephalographic recordings from four epileptic patients, we present evidence that epileptic seizures appear to serve as dynamical resetting mechanisms of the brain, that is the dynamically entrained brain areas before seizures disentrain faster and more frequently (p < 0.05) at epileptic seizures than any other periods. We expect these results to shed light into the mechanisms of epileptogenesis, seizure intervention and control, as well as into investigations of intermittent spatiotemporal state transitions in other complex biological and physical systems.     

Stimulation and measurement patterns versus prior information for fast 3D EIT: A breast screening case study

Imposing prior information is a typical strategy in inverse problems in return for a stable numerical algorithm. For a given imaging system configuration, Picard's stability condition could be deployed as a practical measure of the performance of the system against various priors and noise contaminated measurements. Herein, we make extensive use of this measure to quantify the performance of impedance imaging systems for various injection patterns. In effect, we numerically demonstrate that by varying electrode distributions and numbers, little improvement, if any, in the performance of the impedance imaging system is recorded. In contrast, by using groups of electrodes in the 3D current injection process, a step increase in performance is obtained. Numerical results on a female breast phantom reveal that the performance measure of the imaging system is 15% for a conventional combination of stimulation and prior information, 61% for groups of electrodes and the same prior and 97% for groups of electrodes and a more accurate prior. Finally, since a smaller number of electrodes is involved in the measurement process, a smaller number of measurements is acquired. However, no compromise in the quality of the reconstructed images is observed.     

Dynamical diseases of brain systems: different routes to epileptic seizures

In this overview, we consider epilepsies as dynamical diseases of brain systems since they are manifestations of the property of neuronal networks to display multistable dynamics. To illustrate this concept we may assume that at least two states of the epileptic brain are possible: the interictal state characterized by a normal, apparently random, steady-state electroencephalography (EEG) ongoing activity, and the ictal state, that is characterized by paroxysmal occurrence of synchronous oscillations and is generally called, in neurology, a seizure. The transition between these two states can either occur: 1) as a continuous sequence of phases, like in some cases of mesial temporal lobe epilepsy (MTLE); or 2) as a sudden leap, like in most cases of absence seizures. In the mathematical terminology of nonlinear systems, we can say that in the first case the system's attractor gradually deforms from an interictal to an ictal attractor. The causes for such a deformation can be either endogenous or external. In this type of ictal transition, the seizure possibly may be anticipated in its early, preclinical phases. In the second case, where a sharp critical transition takes place, we can assume that the system has at least two simultaneous interictal and ictal attractors all the time. To which attractor the trajectories converge, depends on the initial conditions and the system's parameters. An essential question in this scenario is how the transition between the normal ongoing and the seizure activity takes place. Such a transition can occur either due to the influence of external or endogenous factors or due to a random perturbation and, thus, it will be unpredictable. These dynamical changes may not be detectable from the analysis of the ongoing EEG, but they may be observable only by measuring the system's response to externally administered stimuli. In the special cases of reflex epilepsy, the leap between the normal ongoing attractor and the ictal attractor is caused by a well-defined external perturbation. Examples from these different scenarios are presented and discussed.     

Power penalty due to the amplitude and phase response ripple of a dispersion compensating fiber Bragg grating for chirped optical signals

A concise method is presented for rigorously calculating the power penalty due to the combined implications of the amplitude and phase response ripples of a dispersion compensating fiber Bragg grating and the chirp of the transmitted optical signal. By using trigonometric series to represent the ripples, the calculated penalty can be positive or negative, as obtained in numerical simulations and measurements, depending on the signal chirp and ripple within the modulated signal bandwidth. An approximate upper bound on the power penalty is also presented as an extension of earlier results that always yield positive penalties. Calculated and measured results are compared for two 10-Gb/s return-to-zero (RZ) signals with distinct chirp properties.     

Movement quantification in epileptic seizures: a new approach to video-EEG analysis

It is common that epileptic seizures induce uncoordinated movement in a patient's body. This movement is a relevant clinical factor in seizure identification. Nevertheless, quantification of this information has not been an object of much attention from the scientific community. In this paper, we present our effort in developing a new approach to the quantification of movement patterns in patients during epileptic seizures. We attach markers at landmark points of a patient's body and use a camera and a commercial video-electroencephalogram (EEG) system to synchronously register EEG and video during seizures. Then, we apply image-processing techniques to analyze the video frames and extract the trajectories of those points that represent the course of the quantified movement of different body parts. This information may help clinicians in seizure classification. We describe the framework of our system and a method of analyzing video in order to achieve the proposed goal. Our experimental results show that our method can reflect quantified motion patterns of epileptic seizures, which cannot be accessed by means of traditional visual inspection of video recordings. We were able, for the first time, to quantify the movement of different parts of a convulsive human body in the course of an epileptic seizure. This result represents an enhanced value to clinicians in studying seizures for reaching a diagnosis.     

Bayesian approaches to phase unwrapping: theoretical study

The problem of phase unwrapping of two-dimensional (2-D) phase signals has gained a considerable interest. It deals with the problem of estimating (reconstructing) an absolute phase from the observation of its noisy principal (wrapped) values. This is an ill-posed problem since many possible solutions correspond to a given observation. Many phase unwrapping algorithms have been proposed relying on different constraints for the phase signal sampling process or the nature (e.g., smoothness, regularity) of the phase signal. We look at these algorithms from the Bayesian point of view (estimation theory) and analyze the role of the prior assumptions, studying their equivalencies to the regularization constraints already used. This study leads to the development of the two new phase unwrapping algorithms which are able to work in quite difficult conditions of aliasing and noise. The theoretical study of the analyzed schemes is illustrated by some experiments on synthetic phase signals     

Block versus trellis: an introduction to coded modulation

Coded modulation has had a very significant impact on the communications scene in the decade or so since its introduction, finding practical applications from voice-band modems for telephone lines to deep-space communications. The paper introduces the principles of coded modulation and describes the two main schemes: block coded modulation (BCM) and trellis coded modulation (TCM). In particular it considers the argument between the proponents of BCM and TCM, and points out some pitfalls in the use of performance measures such as asymptotic coding gain for these schemes. It concludes that in terms of performance versus decoder complexity the schemes seem to be quite close, and the choice of the system designer may be determined by other factors     

Broadcasting info-pages to sensors: efficiency versus energy conservation

In sensor networks applied to monitoring applications, individual sensors may perform preassigned or on-demand tasks, or missions. Data updates (info-pages) may be sent to sensors from a command center, via a time-division broadcast channel. Sensors are normally put in sleep mode when not actively listening, in order to conserve energy in their batteries. Hence, a schedule is required that specifies when sensors should listen for updates and when they should sleep. The performance of such a schedule is evaluated based on data-related costs and sensor-related costs. Data-related costs reflect the obsoleteness of current sensor data, or the delay while sensors wait for updated instructions. Sensor-related costs reflect the energy that sensors consume while accessing the broadcast channel and while switching between the active and sleeping modes (rebooting). Our goal is a schedule with the minimum total cost. Previous related work has explored data-related costs, but listening cost has been addressed only under the assumption that the rebooting operation is free. This paper formulates a new cost model, which recognizes the cost of sensor rebooting. We derive an optimal schedule for the single-sensor setting. We proceed to consider schedules of multiple sensors; we formulate a mathematical program to find an optimal fractional schedule for this setting and provide a solution to the lower bound. Several heuristics for scheduling multiple sensors are introduced and analyzed, and various tradeoffs among the cost factors are demonstrated.