Search results for "signal processing"
showing 10 items of 2451 documents
Signal-to-Noise Ratio in Bandpass Direct-Sequence Spread-Spectrum Modulation Systems
1982
The effects of a linear transmission channel on the performance of a correlator receiver for a direct-sequence spreadspectrum system are analyzed and a complete treatment of the influence of a periodic spreading code is carried out. The output data signal is obtained as a function of the channel characteristic and the code sequence employed; this allows maximizing the output signal level and evaluation of the influence of the synchronization error of the local code. The asymptotic value of the correlation loss has also been derived together with the intersymbol inteference power. The general expression of a figure of merit of the effectiveness of the system is also obtained in simple terms …
Transputer-based parallel system for acquisition and on-line analysis of single-fiber electromyographic signals.
1992
Abstract We describe a transputer-based system suitable for accurate measurements of single-fiber electromyographic jitter. It consists of a conventional electromyograph, a home-made interface and a commercially available transputer-based board installed within a PC/AT compatible. Taking advantage of the concurrent operation of two transputer modules, the system features simultaneous data acquisition and statistical signal processing: while data are acquired and analyzed, a real-time visualization of the signal latency and its variability is provided. In the present configuration, the system can acquire and analyze up to 40,000 consecutive action potentials, which can be grouped into up to …
An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms
2008
This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic s…
Spectrum cartography using adaptive radial basis functions: Experimental validation
2017
In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The perfor…
Adaptive Techniques for Microarray Image Analysis with Related Quality Assessment
2007
We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. We pro- pose the microarray image rotation algorithm (MIRA) and the statis- tical gridding pipeline (SGRIP) as two advanced modules devoted to restoring the original microarray grid orientation and to detecting, the correct geometrical information about each spot of input mi- croarray, respectively. Both solutions work by making use of statis- tical observations, obtaining adaptive and reliable information about each spot property. They improve the performance of the microarray image segmentation pipeline (MISP) we rec…
Online Fault Diagnosis System for Electric Powertrains Using Advanced Signal Processing and Machine Learning
2018
Online condition monitoring and fault diagnosis systems are necessary to prevent unexpected downtimes in critical electric powertrains. The machine learning algorithms provide a better way to diagnose faults in complex cases, such as mixed faults and/or in variable speed conditions. Most of studies focus on training phases of the machine learning algorithms, but the development of the trained machine learning algorithms for an online diagnosis system is not detailed. In this study, a complete procedure of training and implementation of an online fault diagnosis system is presented and discussed. Aspects of the development of an online fault diagnosis based on machine learning algorithms are…
Analysis of Stray Flux Spectral Components in Induction Machines under Rotor Bar Breakages at Various Locations
2018
Induction machines under rotor electrical faults have been subjected to intensive research over the years. It is not only the nature of the fault that makes it important to study, but also the differences observed regarding this fault's effect on the motor's conditions. One of these conditions is the rotor bar breakages at non adjacent positions, which has drawn the attention of researchers due to the false negative diagnostic alarms that may be caused. In this paper, a novel approach is presented aiming to reliably detect this type of fault condition. The proposed method is based on the analysis of specific subcomponents of the stray flux over time. The analysis is implemented on an indust…
LabVIEW modeling and simulation, of the digital filters
2015
In order to study digital filters using virtual instrumentation a simulation program specifically designed for this purpose has been developed. To implement this program means to use the following facilities: studying digital Butterworth filters, Cebyshev, Bessel and Median and change their parameters: bandwidth, order, rank and slope; possibility of changing the input parameters: amplitude, offset and frequency; overlay over the input signal, to one of the types of noise such as white noise, Gaussian white noise and Poisson noise; choosing a type of digital filters: low pass, high pass, band-pass and band stop; waveforms graphical representation of the input and output signals; graphical r…
PPG/ECG Multisite Combo System Based on SiPM Technology
2019
Two versions of a PPG/ECG combined system have been realized and tested. In a first version a multisite system has been equipped by integrating 3 PPG optodes and 3 ECG leads, whereas in another setup a portable version has been carried out. Both versions have been realized by equipping the optical probes with SiPM detectors. SiPM technology is expected to bring relevant advantages in PPG systems and overcome the limitations of physiological information extracted by state of the art PPG, such as poor sensitivity of detectors used for backscattered light detection and motion artifacts seriously affecting the measurements repeatability and pulse waveform stability. This contribution presents t…
A nonstationary model for the analysis of transient speech signals
1987
In this correspondence, a model is presented for the analysis of transient speech signals, which is based on a sum of the impulsive responses corresponding to a number of poles with time-dependent parameters. The aim of this analysis is to obtain discriminative features of the different transient elements of speech.