نتایج جستجو برای: linear superposition method

تعداد نتایج: 2002634  

Journal: :Optics letters 2006
Min Xu

A superposition rule for light scattering by composite particles is presented that expresses the scattering amplitude of a composite particle as a superposition of that of the host particle and those of the shadowed inclusions. The superposition rule is derived for a soft composite particle but also provides insight into light scattering by a general composite scatterer. Favorable comparison wi...

2017
Jun Yang Sun Hong Kwon

Ocean waves can be explained in terms of many factors, including wave spectrum, which has the characteristics of wave height and periodicity, directional spreading function, which has a directional property, and random phase, which randomly represents a certain property. Under the assumption of a linear system, ocean waves show irregular behaviours, which can be observed in the forms of wave sp...

Journal: :AI Commun. 2000
Juan J. Flores J. Cerda

Modeling a system is the first step in reasoning about physical devices. By restricting our domain to linear circuits, we can find an efficient algorithm to do this modeling. The algorithm presented in this article is an efficient implementation of the star-mesh reductions used in Electrical Engineering. By choosing the right representation and based on simple data structures, we can reduce con...

Journal: :Vision Research 1996
KARL-HEINZ BÄUML BRIAN A. WANDELL

We have examined how color appearance varies with spatial pattern. Subjects set color-matches between a uniform, 2 deg matching field and bars within squarewave patterns (1,2 and 4 c/deg) or the superposition of these squarewaves. The matches were set using squarewaves and squarewave mixtures with many different colors and contrasts. The color-matches satisfied the basic properties of a linear ...

2006
Taous-Meriem Laleg Emmanuelle Crépeau Michel Sorine

A simplified model of arterial blood pressure intended for use in model-based signal processing applications is presented. The main idea is to decompose the pressure into two components: a travelling wave describes the fast propagation phenomena predominating during the systolic phase and a windkessel flow represents the slow phenomena during the diastolic phase. Instead of decomposing the bloo...

1998
Kathleen Spaey Chris Blondia

In this paper a method is proposed called circulant matching method to approximate the superposition of a number of discrete time batch Markovian arrival sources by a circulant batch Markovian process while matching the stationary cumulative distribution and the autocorrelation sequence of the input rate process Special attention is paid to periodic sources The method is applied to the superpos...

2011
Jörg Bornschein Marc Henniges Gervasio Puertas Jörg Lücke

The presumably most influential models to describe the response properties of simple-cells in primary visual cortex are independent component analysis (ICA; [1]) and sparse coding (SC; [2]). Since they were first introduced, many studies have critically investigated the different assumptions made by these models (e.g., [3]). However, an assumption that has been so far studied very little is the...

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  • "; pgn_html+=pgn_li; } document.getElementById("pgn-ul").innerHTML=pgn_html var pgn_links = document.querySelectorAll('.mypgn'); pgn_links.forEach(function(pgn_link) { pgn_link.addEventListener('click', paginate) }) } function post_and_fetch(data,url) { showLoading() xhr = new XMLHttpRequest(); xhr.open('POST', url, true); xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8'); xhr.onreadystatechange = function() { if (xhr.readyState === 4 && xhr.status === 200) { var resp = xhr.responseText; resp_json=JSON.parse(resp) resp_place = document.getElementById("search_result_div") resp_place.innerHTML = resp_json['results'] search_meta = resp_json['meta'] update_search_meta(search_meta) update_pagination() hideLoading() } }; xhr.send(JSON.stringify(data)); } function unfilter() { url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":"unfilter", "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } function deactivate_all_bars(){ var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(bar) { bar.dataset.active = false bar.style = "stroke:#71a3c5;" }) } year_chart.on("created", function() { var yrchart = document.querySelectorAll('.ct-bar'); yrchart.forEach(function(check) { check.addEventListener('click', checkIndex); }) }); function checkIndex(event) { var yrchart = document.querySelectorAll('.ct-bar'); var year_bar = event.target if (year_bar.dataset.active == "true") { unfilter_res = unfilter() year_bar.dataset.active = false year_bar.style = "stroke:#1d2b3699;" } else { deactivate_all_bars() year_bar.dataset.active = true year_bar.style = "stroke:#e56f6f;" filter_year = chart_data['labels'][Array.from(yrchart).indexOf(year_bar)] url=/search_year_filter/ var term=document.getElementById("search_meta_data").dataset.term var data={ "year":filter_year, "term":term, "pgn":1 } filtered_res=post_and_fetch(data,url) } } function showLoading() { document.getElementById("loading").style.display = "block"; setTimeout(hideLoading, 10000); // 10 seconds } function hideLoading() { document.getElementById("loading").style.display = "none"; } -->