Search results for "Signal"

Approximation of measurements results of „EMERGENCY” signal reception probability

2017

W artykule przedstawiono wyniki aproksymacji przykładowych danych pomiaru prawdopodobieństwa odbioru sygnału NIEBEZPIECZEŃSTWO. Prawdopodobieństwo to rozpatruje się jako funkcję odległości pomiędzy statkiem powietrznym a systemem naziemnym w ustalonych warunkach pomiaru. Aproksymację danych pomiarowych zrealizowano korzystając z własności funkcji logistycznej. Prawdopodobieństwo jako funkcja odległości pozwala na określenie zasięgu sygnału NIEBEZPIECZEŃSTWO dla zadanego poziomu ufności.

Mesoangioblast stem cells membrane vesicles are carriers for molecules involved in autocrine and paracrine signals

2015

The balance model of honest sexual signaling

2022

Costly signalling theory is based on the idea that individuals may signal their quality to potential mates and that the signal's costliness plays a crucial role in maintaining information content (‘honesty’) over evolutionary time. Whereas costly signals have traditionally been described as ‘handicaps’, here we present mathematical results that motivate an alternative interpretation. We show that under broad conditions, the multiplicative nature of fitness selects for roughly balanced investments in mating success and viability, thereby generating a positive correlation between signal size and quality. This balancing tendency occurs because selection for increased investment in a fitness co…

Saddle index properties, singular topology, and its relation to thermodynamic singularities for aϕ4mean-field model

2004

We investigate the potential energy surface of a ${\ensuremath{\phi}}^{4}$ model with infinite range interactions. All stationary points can be uniquely characterized by three real numbers ${\ensuremath{\alpha}}_{+},{\ensuremath{\alpha}}_{0},{\ensuremath{\alpha}}_{\ensuremath{-}}$ with ${\ensuremath{\alpha}}_{+}+{\ensuremath{\alpha}}_{0}+{\ensuremath{\alpha}}_{\ensuremath{-}}=1$, provided that the interaction strength $\ensuremath{\mu}$ is smaller than a critical value. The saddle index ${n}_{s}$ is equal to ${\ensuremath{\alpha}}_{0}$ and its distribution function has a maximum at ${n}_{s}^{\mathrm{max}}=1∕3$. The density $p(e)$ of stationary points with energy per particle $e$, as well as…

The Complex WKB Method

2019

In this chapter we shall study the exponential growth and asymptotic expansions of exact solutions of second-order differential equations in the semi-classical limit. As an application, we establish a Bohr-Sommerfeld quantization condition for Schrodinger operators with real-analytic complex-valued potentials.

Improved Quadratic Time-frequency Distributions for Detecting Inter-turn Short Circuits of PMSMs in Transient States

2020

This paper aims to improve quadratic time-frequency distributions to adapt condition monitoring of electrical machines in transient states. Short-Time Fourier transform (STFT) has been a baseline signal processing technique for detecting fault characteristic frequencies. However, limits of window sizes due to loss of frequency- or time-resolution, make it hard to capture rapid changes in frequencies. Within this study, Choi-Williams and Wigner-Ville distributions are proposed to effectively detect peaks at characteristic frequencies while still maintaining low computation time. The improved quadratic time-frequency distributions allow for generating spectrograms of a longer lasting data sig…

Model selection using limiting distributions of second-order blind source separation algorithms

2015

Signals, recorded over time, are often observed as mixtures of multiple source signals. To extract relevant information from such measurements one needs to determine the mixing coefficients. In case of weakly stationary time series with uncorrelated source signals, this separation can be achieved by jointly diagonalizing sample autocovariances at different lags, and several algorithms address this task. Often the mixing estimates contain close-to-zero entries and one wants to decide whether the corresponding source signals have a relevant impact on the observations or not. To address this question of model selection we consider the recently published second-order blind identification proced…

Gear classification and fault detection using a diffusion map framework

2015

This article proposes a system health monitoring approach that detects abnormal behavior of machines. Diffusion map is used to reduce the dimensionality of training data, which facilitates the classification of newly arriving measurements. The new measurements are handled with Nyström extension. The method is trained and tested with real gear monitoring data from several windmill parks. A machine health index is proposed, showing that data recordings can be classified as working or failing using dimensionality reduction and warning levels in the low dimensional space. The proposed approach can be used with any system that produces high-dimensional measurement data. peerReviewed

Can back-projection fully resolve polarity indeterminacy of independent component analysis in study of event-related potential?

2011

a b s t r a c t In the study of event-related potentials (ERPs) using independent component analysis (ICA), it is a traditional way to project the extracted ERP component back to electrodes for correcting its scaling (magnitude and polarity) indeterminacy. However, ICA tends to be locally optimized in practice, and then, the back-projection of a component estimated by the ICA can possibly not fully correct its polarity at every electrode. We demonstrate this phenomenon from the view of the theoretical analysis and numerical simulations and suggest checking and modifying the abnormal polarity of the projected component in the electrode field before further analysis. Moreover, when several co…

Determining the number of sources in high-density EEG recordings of event-related potentials by model order selection

2011

To high-density electroencephalography (EEG) recordings, determining the number of sources to separate the signal and the noise subspace is very important. A mostly used criterion is that percentage of variance of raw data explained by the selected principal components composing the signal space should be over 90%. Recently, a model order selection method named as GAP has been proposed. We investigated the two methods by performing independent component analysis (ICA) on the estimated signal subspace, assuming the number of selected principal components composing the signal subspace is equal to the number of sources of brain activities. Through examining wavelet-filtered EEG recordings (128…