Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis

Performance assessment of time–frequency RFI mitigation techniques in microwave radiometry

©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Radio–frequency interference (RFI) signals are a well-known threat for microwave radiometry (MWR) applications. In order to alleviate this problem, different approaches for RFI detection and mitigation are currently under development. Since RFI signals are man made, they tend to have their power more concentrated in the time–frequency (TF) space as compared to naturally emitted noise. The aim of this paper is to perform an assessment of different TF RFI mitigation techniques in terms of probability of detection, resolution loss (RL), and mitigation performance. In this assessment, six different kinds of RFI signals have been considered: a glitch, a burst of pulses, a wide-band chirp, a narrow-band chirp, a continuous wave, and a wide-band modulation. The results show that the best performance occurs when the transform basis has a similar shape as compared to the RFI signal. For the best case performance, the maximum residual RFI temperature is 14.8 K, and the worst RL is 8.4%. Moreover, the multiresolution Fourier transform technique appears as a good tradeoff solution among all other techniques since it can mitigate all RFI signals under evaluation with a maximum residual RFI temperature of 21 K, and a worst RL of 26.3%. Although the obtained results are still far from an acceptable bias Misplaced < 1 K for MWR applications, there is still work to do in a combined test using the information gathered simultaneously by all mitigation techniques, which could improve the overall performance of RFI mitigation.Peer ReviewedPostprint (author's final draft

A semidiscrete version of the Citti-Petitot-Sarti model as a plausible model for anthropomorphic image reconstruction and pattern recognition

In his beautiful book [66], Jean Petitot proposes a sub-Riemannian model for the primary visual cortex of mammals. This model is neurophysiologically justified. Further developments of this theory lead to efficient algorithms for image reconstruction, based upon the consideration of an associated hypoelliptic diffusion. The sub-Riemannian model of Petitot and Citti-Sarti (or certain of its improvements) is a left-invariant structure over the group $SE(2)$ of rototranslations of the plane. Here, we propose a semi-discrete version of this theory, leading to a left-invariant structure over the group $SE(2,N)$, restricting to a finite number of rotations. This apparently very simple group is in fact quite atypical: it is maximally almost periodic, which leads to much simpler harmonic analysis compared to $SE(2).$ Based upon this semi-discrete model, we improve on previous image-reconstruction algorithms and we develop a pattern-recognition theory that leads also to very efficient algorithms in practice.Comment: 123 pages, revised versio

Wavelet based design of digital multichannel communications systems

The huge penetration of the personal communications systems in the market is constantly presenting new challenges to the research, aimed at satisfying people's needs and requirements for effective communication systems. At present, the cellular telephone network is perhaps the most evident example of communication system that has had a great impact on the lives of ordinary people and, at the same time, is the subject of interest of many researchers both at academic and industrial level. For the future, one of the main challenges in telecommunications will be the provision of ubiquitous broadband tetherless integrated services to mobile users. Such a pretentious goal cannot be achieved without a continuous research facing such problems as service quality, complete mobility support, and affordable complexity that are still open problems. However, present telecommunication problems are not only a matter of implementation or development of new services, exploiting a totally assessed doctrine. In order to respond to the mobility of the users personal communication systems have to deal with the wireless communication channel whereby mobility and non-stationarity of the propagation conditions require a stochastic description of the channel parameters. While this fact can be viewed as strong limitation to the development of a solid theory whose validity can be assesed in practice, on the other hand allows for an investigation and study of novel communication schemes, sometimes encompassing basic aspects of digital communications. This thesis, is the result of a research work that has investigated one of the basic building block of every communication systems, the modulation scheme, and the design of the pulse shape carrying the digital information. We have studied the design of multichannel communication scheme exploiting the mathematical theory of wavelets. Such a theory, developed recently, has had a great impact in many fields of engineering and of other scientific disciplines. In particular, wavelet theory has become very popular in the signal processing area; in fact it is a flexible toolbox for signal analysis allowing effective representation of signals for features extraction purposes. The main features that make wavelet waveforms suitable to be used as shaping pulses for modulation are their substantial compact support both in the time and frequency domains, and the fact that they are ISI-free pulses over frequency flat channels. The study presented in this thesis is focused on application of wavelet theory to design high-efficiency multichannel communication schemes and to the performance evaluation over linear and non-linear channels. We present a general method to design wavelet based multichannel communication schemes that we denoted Wavelet Orthogonal Frequency Division Multiplexing (WOFDM). We show that such schemes, having a largerspectral efficiency for a small number of channels, are a valid alternative to the classical OFDM. Potential advantage of wavelet modulation are shown presenting other applications examined in this thesis: a joint use of WOFDM and Trellis Coded Modulation to shape the power spectrum in order to match a frequency selective channel and minimize distortion, and application to spread spectrum modulation. Particular attention has been devoted to the timing recovery problem in multichannel communication schemes, exploiting the timing information of the different subchannels to improve the error variance in estimation of the sampling instant leading to a reduction of the adjacent channels interferenc

Measurements, Models, Systems and Design

531 s.

Digital Filters and Signal Processing

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies. They present the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed worldwide