The paper presents a LOFAR Beamforming Simulator software developed for simulation of beamforming which can be used for enhancement of radiolocation capabilities of radioastronomical LOFAR station in the context of its use for passive radiolocation. The great challenge of ongoing research on such use of LOFAR stations is to collect sufficient, real LOFAR data to analyze countless cases that can occur in passive radar scenarios. For this reason, simulation of various cases is the most efficient way to analyse and to ascertain what can happen if these cases occur in the future in real passive radar systems. The operation principles and capabilities of the LOFAR Beamforming Simulator are described in this paper. The comparison of simulated results with equivalent, real ones confirms the corectness of the designed software.
This paper presents results of verification of human subjects, using electroencephalography (EEG) signals taken from frontal electrodes. Although we performed examinations with a full EEG 10-20 montage system, we decided to assess the results obtained from different small sets of frontal electrodes to consider subset of electrodes which would have the performance in people verification system based on their EEG signals. Additionally, for reference, we included results achieved from all 19 electrodes. The sets of electrodes were chosen for their easy access and the possibility of using in commercially available EEG headsets or bundles. Over 700 examinations were collected from 36 healthy adults (almost 20 EEG sessions were recorded from each person). The first 15 examinations from each participant were used for training the feedforward neural network with the Levenberg-Marquardt backpropagation algorithm. For each person, the different neural network was created. In the next step, people were verified using these networks by means of statistical metrics evaluation. The metrics were calculated using examinations which were recorded on different days both for the training and testing sets. Thanks to this approach, we were able to exclude the impact of daily changes in EEG and to get closer to the actual use of such a system. In this preliminary study, we focused on spectral features of EEG signals, to investigate whether temporary changes would prevent people from being recognized. Due to the large dataset, this paper can be the introduction for further works on searching and selecting features that will allow verification and will be invariable in time.
The results of experimental studies on application of selected simple machine learning (ML) methods for detection of atrial fibrillation (AFib) based on photoplethysmogram (PPG) are presented in the paper. The goal of the studies was to compare the performance of AFib detection using different ML algorithms in short PPG segments containing 32 consecutive cardiac cycles. Four parameters describing time series of interbeat intervals (IBI) were derived from the time domain Heart Rate Variability (HRV) and used as features for classification algorithms. Optimal values of metaparameters for all considered ML algorithms were experimentally determined. Accuracy, sensitivity, specificity and F1-score were then calculated to measure the quality of detection performance of each classification algorithm.
KEYWORDS: Electroencephalography, Electronic filtering, Digital filtering, Linear filtering, Signal processing, Filtering (signal processing), Digital signal processing
This paper presents the evaluation of adaptive filtering methods for suppression of the second powerline harmonic in electroencephalography (EEG) signals. The powerline interference with its harmonics is the most frequent noise source distorting EEG signals. Mostly its power is too high, to be simply removed by a low-pass filter, especially during the analysis of upper gamma frequencies (up to 100 Hz), where some information about EEG signal could be lost. This paper focuses on comparison of the adaptive algorithms (Least Mean Squares (LMS), and Recursive Least Squares (RLS)) in the suppression of harmonic interferences. This evaluation is based on the dedicated measures, allowing to assess the distortions remaining after the powerline suppression. The results of studies confirm the usability of the adaptive filters in powerline and its harmonics suppression.
The paper presents a new method for autocalibration of offsets of internal components in adaptive sub-ranging analog-todigital
converters (ADCs). The adaptive sub-ranging ADCs, like other iterative ADCs, are very sensitive to offsets
caused by technological imperfections. To achieve higher effective resolution in a sub-ranging ADC, offsets should be
accordingly diminished, which is achieved using sophisticated techniques usually causing increase of power
consumption as well as complexity and size of ADC. But the structure of adaptive sub-ranging ADC and the way of
calculation of output codes create a possibility to compensate offsets during conversion of input samples. Moreover,
using the internal digital-to-analog converter (DAC) as a source of calibration signal in the procedure of offsets
estimation and addition of a calibration program in the digital part of the converter, enable automatization and
autonomization (no additional instruments are needed) of the calibration process. Usefulness and limitations of the
proposed solution were confirmed in computer simulations whose main results are presented and discussed in the paper.
Implementation of the proposed solution enables to increase effective resolution of ADCs and simultaneously to weaken
the requirements on acceptable level of offsets of ADC components.
KEYWORDS: Microcontrollers, Fourier transforms, Signal processing, Digital signal processing, Interfaces, Analog electronics, Clocks, Statistical analysis, Intelligence systems, Oscilloscopes
In this paper, a real-time implementation of pitch shifting with use of phase vocoder algorithm is presented. The goal was to create a system that would allow to process audio signal in real time with use of a general purpose microcontroller. The task was a challenge due to relative complexity of the algorithm and limited computational capacity of the microcontroller, whose architecture is by nature much more universal than that of dedicated digital signal processors. The results of experiments with the developed system are presented and discussed in the paper.
The paper presents the results of studies pertaining to the influence of gain errors of inter-stage amplifiers on performance of adaptive sub-ranging analog-to-digital converters (ADCs). It focuses on adaptive sub-ranging ADCs with simplified architecture of the analog part – using only one amplifier and a low resolution digital-to-analog converter, that is identical to that of known conventional sub-ranging ADCs. The only difference between adaptive subranging ADCs with simplified architecture and conventional sub-ranging ADCs is the process of determination of output codes of converted samples. The adaptive sub-ranging ADCs calculate the output codes on the basis of sub-codes obtained in particular stages of conversion using an adaptive algorithm. Thanks to application of the optimal adaptive algorithm, adjusted to the parameters of possible components imperfections and internal noises, the adaptive ADCs outperform, in terms of effective resolution per cycle, conventional sub-ranging ADCs forming the output codes using simple lower-level bit operations. Optimization of the conversion algorithm used in adaptive ADCs leads however to high sensitivity of adaptive ADCs performance to the inter-stage gain error. An effective method for reduction of this sensitivity in adaptive sub-ranging ADCs with simplified architecture is proposed and discussed in the paper.
KEYWORDS: Digital signal processing, Fourier transforms, Continuous wavelet transforms, Signal processing, Wavelets, Time-frequency analysis, Statistical analysis, Signal analyzers, Wavelet transforms
In this paper, we present the techniques used for modifying the spectral content (pitch shifting) and for changing the time duration (time scaling) of an audio signal. A short introduction gives a necessary background for understanding the discussed issues and contains explanations of the terms used in the paper. In subsequent sections we present three different techniques appropriate both for pitch shifting and for time scaling. These techniques use three different time-frequency representations of a signal, namely short-time Fourier transform (STFT), continuous wavelet transform (CWT) and constant-Q transform (CQT). The results of simulation studies devoted to comparison of the properties of these methods are presented and discussed in the paper.
One of the constraints in manufacturing of sub-ranging ADCs with high ENOB, is a necessity to provide that the internal components have very small offsets. Application of readily available solutions consisting in designing “large” components or using dynamic offset cancelation techniques, increases die size and power consumption. The paper proposes an alternative approach free of these unwanted consequences. There are developed and analyzed three methods of reduction of the influence of offsets on the performance of adaptive sub-ranging ADCs that do not require any changes in the structure of their analog part, varying in whether and where the offsets are compensated. On the basis of the results of simulation analysis, we recommend the latter of the examined methods as most preferable in all conditions, enabling elimination of the influence of offsets to the extent depending on the accuracy of their postproduction measurement and representation in the digital part of the converter. Its application allows improvement of achievable ENOB and significant weakening of the requirements to offsets of the internal components and, in effect, reduction of power consumption and manufacturing costs of the adaptive sub-ranging ADCs.
The paper presents the results of studies on the behavior of adaptive cyclic analog-to-digital converters (ADCs) for greater number of cycles (iterations) of the sample conversion. A distinguishing feature of the adaptive cyclic ADCs is iterative calculation of output codes of converted samples using a simple digital processing unit (DPU) according to dedicated conversion algorithm. Previous research showed that application of DPU extends radically the possibility of analytical and simulation analysis of cyclic ADCs functioning and allows to improve the effective resolution of the ADCs in comparison with similar conventional sub-ranging cyclic ADCs forming the output codes using logic elements. Moreover, DPU and possibility of optimization of the adaptive cyclic ADCs create a number of new effects important for applications, unachievable in known cyclic ADCs. One of them is restoration of monotonic growth of the adaptive cyclic ADC resolution in the "post-threshold" cycles of conversion, where resolution of conventional cyclic ADCs is fixed without possibility of improvement by increasing number of cycles. In the paper, there is proposed and analyzed a new conversion algorithm for the adaptive cyclic ADCs that combines the most desired features of the algorithms developed earlier, i.e. provides the greatest possible rate of increase of effective number of bits (ENOB) of ADC in the initial "pre-threshold" phase of conversion, and enables further increase of ENOB in the "post-threshold" phase.
KEYWORDS: Digital signal processing, Signal processing, Microcontrollers, Analog electronics, Real-time computing, Computer simulations, Reflection, MATLAB, Acoustics, Linear filtering
The paper is devoted to studies on possibilities of realization of guitar audio effects by means of methods of digital signal processing. As a result of research, some selected audio effects corresponding to the specifics of guitar sound were realized as the real-time system called Digital Guitar Multi-effect. Before implementation in the system, the selected effects were investigated using the dedicated application with a graphical user interface created in Matlab environment. In the second stage, the real-time system based on a microcontroller and an audio codec was designed and realized. The system is designed to perform audio effects on the output signal of an electric guitar.
The paper discusses the possibility of application of nonlinearity measures – INL and DNL, as recommended in IEEE Std 1241, to adaptive cyclic ADC. The first difficulty confronted was not knowing the nominal transfer function of adaptive ADC. To overcome this difficulty, there was proposed an algorithm for its analytical determination on the basis of the models and parameters of the components of the analog part of the converter and of the codes computing algorithm. Using this tool, validated in simulation experiments, there was established a non-uniformity of the adaptive ADC nominal transfer function, concerning both thresholds and quantization levels. The latter is the second, unremovable obstacle to application of INL and DNL measures to characterization of adaptive ADC nonlinearity. In the paper, there are explained the causes of the non-uniformity and there is shown a possibility and conditions of realization of adaptive ADCs with uniform nominal transfer function. Finally, there are presented the results of simulation analysis of the influence of the established non-uniformity of nominal transfer function of adaptive ADC on THD - another popular measure of ADC nonlinearity recommended in IEEE Std 1241 - which show that the non-uniformity does not worsen THD compared with THD obtained for adaptive ADC with similar but uniform transfer function.
KEYWORDS: Analog electronics, Statistical analysis, Algorithm development, Quantization, Digital signal processing, Binary data, Amplifiers, Optimization (mathematics), Error analysis, Signal processing
The paper presents the survey of architectures and conversion algorithms used in so called adaptive analog-to-digital
converters considered during the studies on these converters carried out by the author and his colleagues. The key idea
that distinguishes the adaptive analog-to-digital converters from other sub-ranging converters consists in application
of the iterative digital signal processing algorithm for calculation of the output codes of the converters and for calculation
of the values of residue signal gains in subsequent steps of conversion. Application of this approach in the proposed
converters allows to achieve better parameters of the converters in comparison with parameters of conventional sub-ranging
analog-to-digital converters.
The paper presents the results of investigations on the new approach to optimization of sub-ranging analog-to-digital converters (ADCs) working with the assumed level of their components imperfections caused by technological dispersions, errors, noises or disturbances. The suggested approach is based on application of digital estimation algorithms that take into consideration the anticipated parameters of the components imperfections. Implementation of the approach is possible in the sub-ranging ADCs whose digital parts permit to calculate output codes of ADCs by means of simple mathematical operation. The performance of ADCs operating according to this approach is analyzed for the imperfections of different ADC components in simulation experiments. The results obtained for the proposed ADC are compared with the results obtained for the conventional pipeline ADC employing the identical analog components.
KEYWORDS: Analog electronics, Amplifiers, Binary data, Optimization (mathematics), Quantization, Statistical analysis, Data communications, Error analysis, Information technology, Testing and analysis
The paper presents a new approach to improvement of pipeline analog-to-digital (A/D) converters characteristics.
The approach is based on application of adaptive estimation algorithms to control and calculate output codes of pipeline
A/D converters. Implementation of adaptive algorithms is possible in so called intelligent pipeline A/D converters (IP
ADCs) whose digital parts permit to calculate iteratively output codes in form of binary words using simple
mathematical operations. This paper develops the earlier research on IP ADCs and removes some disadvantages of
conventional IP ADCs simplifying their architecture and increasing achievable values of effective number of bits
(ENOB) of converters. Results of selected simulation experiments illustrating new effects related to application of the
proposed solutions and their potential benefits are also presented and discussed in the paper.
The paper presents a new approach to reduction of influence of disturbances on performance of cyclic analog-to-digital
converters (ADC). The approach is based on application of multidimensional estimation algorithms for simultaneous
estimation of both input sample value and parameters of disturbances. Implementation of these algorithms is possible in
a new class of adaptive cyclic ADCs whose digital parts permit to calculate iteratively output codes in form of binary
words using simple mathematical operations. Estimation of parameters of disturbances enables their compensation and
elimination of their influence on the conversion performance. Results of selected simulation experiments related to
analysis of the efficiency of the proposed method in reduction of disturbances influence on final performance of adaptive
cyclic ADCs are also presented and discussed in the paper.
The paper presents a brief survey of new results in the theory, modelling, implementation and testing of new class of high-efficient low-energy cyclic A/D converters (CADC) - "intelligent" cyclic ADC (IC ADC). There are discussed general principles of IC ADC functioning, analysis and design, Advantages of IC ADC over conventional CADC caused by transition to computing of the long-bit codes (estimates) of the input signal are explained. Special attention is paid to particularities and methods of modelling analysis and testing of IC ADC.
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