Search results for "algorithm"
showing 10 items of 4887 documents
Untersuchungen zur Reliabilität von Mustererkennungs-Algorithmen für die P-Wellen orthogonaler Elektrokardiogramme
1979
On the Reliability of Pattern Recognition Algorithms for ECGs Judging the performance of pattern recognition algorithms in ECG analysis on an objective basis still presents a severe problem because of the heuristic nature of the criteria used- The paper illustrates that problem by way of P-wave detectors for ECGs. We want to focus on the external reliability of the algorithms. The term external reliability is closely related to condition or robustness. Here we are interested in the variation of the output of an algorithm when the input data are slightly altered. This pertains to the problem of how the biological variance of the ECGs is mapped into the variance of algorithm output. We may sa…
A random-walk benchmark for single-electron circuits
2021
Mesoscopic integrated circuits aim for precise control over elementary quantum systems. However, as fidelities improve, the increasingly rare errors and component crosstalk pose a challenge for validating error models and quantifying accuracy of circuit performance. Here we propose and implement a circuit-level benchmark that models fidelity as a random walk of an error syndrome, detected by an accumulating probe. Additionally, contributions of correlated noise, induced environmentally or by memory, are revealed as limits of achievable fidelity by statistical consistency analysis of the full distribution of error counts. Applying this methodology to a high-fidelity implementation of on-dema…
Scatter Search Applications
2003
This section provides a collection of “vignettes” that briefly summarize applications of scatter search (SS) and path relinking (PR) in a variety of settings.
Extracting cloud motion from satellite image sequences
2004
This paper present a new technique for the estimation of cloud motion, using a sequence of infrared satellite images. It can be considered a challenging task due to the complexity of phenomena implied, as non-linear events and a non-rigid motion. In this circumstances most motion models are not suitable and new algorithms have to be developed. We propose a novel method, combining an Automatic Multilevel Thresholding for image segmentation, a Block Matching Algorithm (BMA) and a best candidate block search along with a vector median regularization.
What is the Natural Abstraction Level of an Algorithm?
2021
Abstract State Machines work with algorithms on the natural abstraction level. In this paper, we discuss the notion of the natural abstraction level of an algorithm and how ASM manage to capture this abstraction level. We will look into three areas of algorithms: the algorithm execution, the algorithm description, and the algorithm semantics. We conclude that ASM capture the natural abstraction level of the algorithm execution, but not necessarily of the algorithm description. ASM do also capture the natural abstraction level of execution semantics.
Spectrogram analysis of multipath fading channels
2015
The analysis of the Doppler power spectral density (PSD) of measured and simulated data is an important topic in the area of mobile radio channel modelling. In this paper, we estimate the Doppler PSD of multipath fading channels by using the concept of the spectrogram. The spectrogram is a spectral representation that gives insight into how the distribution of the spectral density of a signal changes over time. The multipath fading channel is modelled by a sum-of-cisoids (SOC) process. A closed-form solution is presented for the spectrogram and the corresponding time-dependent autocorrelation function (ACF). The closed-form solutions disclose several unwanted effects that come with the limi…
Atrial activity extraction for atrial fibrillation analysis using blind source separation.
2004
This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA …
Automatic fitting of cochlear implants with evolutionary algorithms
2004
This paper presents an optimisation algorithm designed to perform in-situ automatic fitting of cochlear implants.All patients are different, which means that cochlear parametrisation is a difficult and long task, with results ranging from perfect blind speech recognition to patients who cannot make anything out of their implant and just turn it off.The proposed method combines evolutionary algorithms and medical expertise to achieve autonomous interactive fitting through a Personal Digital Assistant (PDA).
An Information-Theoretic Framework to Measure the Dynamic Interaction between Neural Spike Trains
2021
Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumptions that may lead to wrong inferences if not met. This work presents a framework, grounded in the field of information dynamics, for the model-free, continuous-time estimation of both undirected (symmetric) and directed (causal) interactions between pairs of spike trains. The framework decomposes the overall information exchanged dynami…
Testing for goodness rather than lack of fit of continuous probability distributions.
2021
The vast majority of testing procedures presented in the literature as goodness-of-fit tests fail to accomplish what the term is promising. Actually, a significant result of such a test indicates that the true distribution underlying the data differs substantially from the assumed model, whereas the true objective is usually to establish that the model fits the data sufficiently well. Meeting that objective requires to carry out a testing procedure for a problem in which the statement that the deviations between model and true distribution are small, plays the role of the alternative hypothesis. Testing procedures of this kind, for which the term tests for equivalence has been coined in sta…