Low voltage analog synthesizer of orthogonal signals: A current-mode approach

An analog synthesizer of orthogonal signals for digital CMOS technology and 3V supply voltage is presented. The adaptive architecture accomplishes the synthesis of mutually orthogonal signal, such as trigonometric and polynomial basis. Experimental results using 0.35 mu m AMS CMOS process are presented for generation of the cosine and Legendre basis.

Low voltage analog synthesizer of orthogonal signals using current mode techniques

An analog synthesizer of orthogonal signals for digital CMOS technology and 3V supply voltage is presented. The adaptive architecture accomplishes the synthesis of mutually orthogonal signal, such as trigonometric and polynomial basis. Simulation results using 0.35 mu m AMS CMOS process are presented for generation of the cosine and Legendre basis.

Sintetizador analógico de sinais ortogonais: projeto e construção usando tecnologia CMOS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Better QOS with W/T SPR codes for the transmission of multimedia signals in Optical CDMA networks

In this paper optical code-division multiple-access (O-CDMA) packet network is considered, which offers inherent security in the access networks. The application of O-CDMA to multimedia transmission (voice, data, and video) is investigated. The simultaneous transmission of various services is achieved by assigning to each user unique multiple code signatures. Thus, by applying a parallel mapping technique, we achieve multi-rate services. A random access protocol is proposed, here, where all distinct codes are used, for packet transmission. The codes, Optical Orthogonal Code (OOC), or 1D codes and Wavelength/Time Single-Pulse-per-Row (W/T SPR), or 2D codes, are analyzed. These 1D and 2D codes with varied weight are used to differentiate the Quality of Service (QoS). The theoretical bit error probability corresponding to the quality of each service is established using 1D and 2D codes in the receiver noiseless case and compared. The results show that, using 2D codes QoS in multimedia transmission is better than using 1D codes.

Feedback communication using orthogonal signals

This research is concerned with block coding for a feedback communication system in which the forward and feedback channels are independently disturbed by additive white Gaussian noise and average power constrained. Two coding schemes are proposed in which the messages to be coded for transmission over the forward channel are realized as a set of orthogonal waveforms. A finite number of forward and feedback transmissions (iterations) per message is made. Information received over the feedback channel is used to modify the waveform transmitted on successive forward iterations in such a way that the expected value of forward signal energy is zero on all iterations after the first. Similarly, information is sent over the feedback channel in such a way that the expected value of feedback signal energy is also zero on all iterations after the first. These schemes are shown to achieve a lower probability of error than the best one-way coding scheme at all rates up to the forward channel capacity, provided only that the feedback channel capacity be greater than the forward channel capacity. These schemes make more efficient use of the available feedback power than existing feedback coding schemes, and therefore require less feedback power to achieve a given error performance.

Context-Based Modelling of Interferometric Signals for the Assessment of Tear-Film Suface Quality

Modelling of interferometric signals related to tear film surface quality is considered. In the context of tear film surface quality estimation in normal healthy eyes, two clinical parameters are of interest: the build-up time, and the average interblink surface quality. The former is closely related to the signal derivative while the latter to the signal itself. Polynomial signal models, chosen for a particular set of noisy interferometric measurements, can be optimally selected, in some sense, with a range of information criteria such as AIC, MDL, Cp, and CME. Those criteria, however, do not always guarantee that the true derivative of the signal is accurately represented and they often overestimate it. Here, a practical method for judicious selection of model order in a polynomial fitting to a signal is proposed so that the derivative of the signal is adequately represented. The paper highlights the importance of context-based signal modelling in model order selection.

Analysis of phasor measurement method in tracking the power frequency of distorted signals

This paper presents an analysis of phasor measurement method for tracking the fundamental power frequency to show if it has the performance necessary to cope with the requirements of power system protection and control. In this regard, several computer simulations presenting the conditions of a typical power system signal especially those highly distorted by harmonics, noise and offset, are provided to evaluate the response of the Phasor Measurement (PM) technique. A new method, which can shorten the delay of estimation, has also been proposed for the PM method to work for signals free of even-order harmonics.

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.

A Bias in ML Estimates of Branch Lengths in the Presence of Multiple Signals

Sequence data often have competing signals that are detected by network programs or Lento plots. Such data can be formed by generating sequences on more than one tree, and combining the results, a mixture model. We report that with such mixture models, the estimates of edge (branch) lengths from maximum likelihood (ML) methods that assume a single tree are biased. Based on the observed number of competing signals in real data, such a bias of ML is expected to occur frequently. Because network methods can recover competing signals more accurately, there is a need for ML methods allowing a network. A fundamental problem is that mixture models can have more parameters than can be recovered from the data, so that some mixtures are not, in principle, identifiable. We recommend that network programs be incorporated into best practice analysis, along with ML and Bayesian trees.

Bayesian refinement of association signals for 14 loci in 3 common diseases

To further investigate susceptibility loci identified by genome-wide association studies, we genotyped 5,500 SNPs across 14 associated regions in 8,000 samples from a control group and 3 diseases: type 2 diabetes (T2D), coronary artery disease (CAD) and Graves' disease. We defined, using Bayes theorem, credible sets of SNPs that were 95% likely, based on posterior probability, to contain the causal disease-associated SNPs. In 3 of the 14 regions, TCF7L2 (T2D), CTLA4 (Graves' disease) and CDKN2A-CDKN2B (T2D), much of the posterior probability rested on a single SNP, and, in 4 other regions (CDKN2A-CDKN2B (CAD) and CDKAL1, FTO and HHEX (T2D)), the 95% sets were small, thereby excluding most SNPs as potentially causal. Very few SNPs in our credible sets had annotated functions, illustrating the limitations in understanding the mechanisms underlying susceptibility to common diseases. Our results also show the value of more detailed mapping to target sequences for functional studies. © 2012 Nature America, Inc. All rights reserved.

ANC schemes for the enhancement of EEG signals in the presence of EOG artifacts

One of the most important applications of adaptive systems is in noise cancellation using adaptive filters. Ln this paper, we propose adaptive noise cancellation schemes for the enhancement of EEG signals in the presence of EOG artifacts. The effect of two reference inputs is studied on simulated as well as recorded EEG signals and it is found that one reference input is enough to get sufficient minimization of EOG artifacts. This has been verified through correlation analysis also. We use signal to noise ratio and linear prediction spectra, along with time plots, for comparing the performance of the proposed schemes for minimizing EOG artifacts from contaminated EEG signals. Results show that the proposed schemes are very effective (especially the one which employs Newton's method) in minimizing the EOG artifacts from contaminated EEG signals.

Comparative study of filter-bank mean-energy distance for automated segmentation of speech signals

This paper describes a method of automated segmentation of speech assuming the signal is continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the 'Bach' (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. 'Bach' filters are seen to marginally outperform the other filters.