Molecular phase space transport in water:non-stationary random walk model

Molecular transport in phase space is crucial for chemical reactions because it defines how pre-reactive molecular configurations are found during the time evolution of the system. Using Molecular Dynamics (MD) simulated atomistic trajectories we test the assumption of the normal diffusion in the phase space for bulk water at ambient conditions by checking the equivalence of the transport to the random walk model. Contrary to common expectations we have found that some statistical features of the transport in the phase space differ from those of the normal diffusion models. This implies a non-random character of the path search process by the reacting complexes in water solutions. Our further numerical experiments show that a significant long period of non-stationarity in the transition probabilities of the segments of molecular trajectories can account for the observed non-uniform filling of the phase space. Surprisingly, the characteristic periods in the model non-stationarity constitute hundreds of nanoseconds, that is much longer time scales compared to typical lifetime of known liquid water molecular structures (several picoseconds).

Bootstrap for Critical Branching Process with Non-Stationary Immigration

2000 Mathematics Subject Classification: Primary 60J80, Secondary 62F12, 60G99.

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations.

A Review of ENSO Influence on the North Atlantic. A Non-Stationary Signal

The atmospheric seasonal cycle of the North Atlantic region is dominated by meridional movements of the circulation systems: from the tropics, where the West African Monsoon and extreme tropical weather events take place, to the extratropics, where the circulation is dominated by seasonal changes in the jetstream and extratropical cyclones. Climate variability over the North Atlantic is controlled by various mechanisms. Atmospheric internal variability plays a crucial role in the mid-latitudes. However, El Niño-Southern Oscillation (ENSO) is still the main source of predictability in this region situated far away from the Pacific. Although the ENSO influence over tropical and extra-tropical areas is related to different physical mechanisms, in both regions this teleconnection seems to be non-stationary in time and modulated by multidecadal changes of the mean flow. Nowadays, long observational records (greater than 100 years) and modeling projects (e.g., CMIP) permit detecting non-stationarities in the influence of ENSO over the Atlantic basin, and further analyzing its potential mechanisms. The present article reviews the ENSO influence over the Atlantic region, paying special attention to the stability of this teleconnection over time and the possible modulators. Evidence is given that the ENSO–Atlantic teleconnection is weak over the North Atlantic. In this regard, the multidecadal ocean variability seems to modulate the presence of teleconnections, which can lead to important impacts of ENSO and to open windows of opportunity for seasonal predictability.

The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis

Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MAT-LAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/(Mentaschi et al., 2016).

Analysis of Non-Stationary Flows Using Eulerian and Lagrangian Frameworks

Recent developments have made researchers to reconsider Lagrangian measurement techniques as an alternative to their Eulerian counterpart when investigating non-stationary flows. This thesis advances the state-of-the-art of Lagrangian measurement techniques by pursuing three different objectives: (i) developing new Lagrangian measurement techniques for difficult-to-measure, in situ flow environments; (ii) developing new post-processing strategies designed for unstructured Lagrangian data, as well as providing guidelines towards their use; and (iii) presenting the advantages that the Lagrangian framework has over their Eulerian counterpart in various non-stationary flow problems. Towards the first objective, a large-scale particle tracking velocimetry apparatus is designed for atmospheric surface layer measurements. Towards the second objective, two techniques, one for identifying Lagrangian Coherent Structures (LCS) and the other for characterizing entrainment directly from unstructured Lagrangian data, are developed. Finally, towards the third objective, the advantages of Lagrangian-based measurements are showcased in two unsteady flow problems: the atmospheric surface layer, and entrainment in a non-stationary turbulent flow. Through developing new experimental and post-processing strategies for Lagrangian data, and through showcasing the advantages of Lagrangian data in various non-stationary flows, the thesis works to help investigators to more easily adopt Lagrangian-based measurement techniques.

An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data

Min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA) are complementary techniques for analysing short (> 15-25 y), non-stationary, multivariate data sets. We illustrate the two techniques using catch rate (cpue) time-series (1982-2001) for 17 species caught during trawl surveys off Mauritania, with the NAO index, an upwelling index, sea surface temperature, and an index of fishing effort as explanatory variables. Both techniques gave coherent results, the most important common trend being a decrease in cpue during the latter half of the time-series, and the next important being an increase during the first half. A DFA model with SST and UPW as explanatory variables and two common trends gave good fits to most of the cpue time-series. (c) 2004 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

Sportliche Leistungsfähigkeit und zeitabhängiges Frequenzverhalten von Oberflächenelektromyogrammen

Electromyography, EMG, spectral analysis, median frequency, non-stationary signals, sports performance, modelling, simulation, intramuscular coordination, motor unit, fuzzy control

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Spectral analysis and low-frequency multipath mitigation for kinematic applications

Low-frequency multipath is still one of the major challenges for high precision GPS relative positioning. In kinematic applications, mainly, due to geometry changes, the low-frequency multipath is difficult to be removed or modeled. Spectral analysis has a powerful technique to analyze this kind of non-stationary signals: the wavelet transform. However, some processes and specific ways of processing are necessary to work together in order to detect and efficiently mitigate low-frequency multipath. In this paper, these processes are discussed. Some experiments were carried out in a kinematic mode with a controlled and known vehicle movement. The data were collected in the presence of a reflector surface placed close to the vehicle to cause, mainly, low-frequency multipath. From theanalyses realized, the results in terms of double difference residuals and statistical tests showed that the proposed methodology is very efficient to detect and mitigate low-frequency multipath effects. © 2008 IEEE.

Characterizing background heterogeneity in visual communication

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Marine mammal species detection and classification

Thesis (Ph.D.)--University of Washington, 2016-04

Tracking the states of a nonlinear system in the weight-space of a feed-forward neural network

Nonlinear, non-stationary signals are commonly found in a variety of disciplines such as biology, medicine, geology and financial modeling. The complexity (e.g. nonlinearity and non-stationarity) of such signals and their low signal to noise ratios often make it a challenging task to use them in critical applications. In this paper we propose a new neural network based technique to address those problems. We show that a feed forward, multi-layered neural network can conveniently capture the states of a nonlinear system in its connection weight-space, after a process of supervised training. The performance of the proposed method is investigated via computer simulations.

A Hybrid Architecture for Recognising Speech Signals in Malayalam

Speech is the primary, most prominent and convenient means of communication in audible language. Through speech, people can express their thoughts, feelings or perceptions by the articulation of words. Human speech is a complex signal which is non stationary in nature. It consists of immensely rich information about the words spoken, accent, attitude of the speaker, expression, intention, sex, emotion as well as style. The main objective of Automatic Speech Recognition (ASR) is to identify whatever people speak by means of computer algorithms. This enables people to communicate with a computer in a natural spoken language. Automatic recognition of speech by machines has been one of the most exciting, significant and challenging areas of research in the field of signal processing over the past five to six decades. Despite the developments and intensive research done in this area, the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level. The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam.

Large aperture antenna arrays with subband delay compensation for reception of wideband satellite signals

Con esta disertación se pretenden resolver algunos de los problemas encontrados actualmente en la recepción de señales de satélites bajo dos escenarios particularmente exigentes: comunicaciones de Espacio Profundo y en banda Ka. Las comunicaciones con sondas de Espacio Profundo necesitan grandes aperturas en tierra para poder incrementar la velocidad de datos. La opción de usar antennas con diámetro mayor de 35 metros tiene serios problemas, pues antenas tan grandes son caras de mantener, difíciles de apuntar, pueden tener largos tiempo de reparación y además tienen una efeciencia decreciente a medida que se utilizan bandas más altas. Soluciones basadas en agrupaciones de antenas de menor tamaño (12 ó 35 metros) son mas ecónomicas y factibles técnicamente. Las comunicaciones en banda Ka tambien pueden beneficiarse de la combinación de múltiples antennas. Las antenas de menor tamaño son más fáciles de apuntar y además tienen un campo de visión mayor. Además, las técnicas de diversidad espacial pueden ser reemplazadas por una combinación de antenas para así incrementar el margen del enlace. La combinación de antenas muy alejadas sobre grandes anchos de banda, bien por recibir una señal de banda ancha o múltiples de banda estrecha, es complicada técnicamente. En esta disertación se demostrará que el uso de conformador de haz en el dominio de la frecuencia puede ayudar a relajar los requisitos de calibración y, al mismo tiempo, proporcionar un mayor campo de visión y mayores capacidades de ecualización. Para llevar esto a cabo, el trabajo ha girado en torno a tres aspectos fundamentales. El primero es la investigación bibliográfica del trabajo existente en este campo. El segundo es el modelado matemático del proceso de combinación y el desarrollo de nuevos algoritmos de estimación de fase y retardo. Y el tercero es la propuesta de nuevas aplicaciones en las que usar estas técnicas. La investigación bibliográfica se centra principalmente en los capítulos 1, 2, 4 y 5. El capítulo 1 da una breve introducción a la teoría de combinación de antenas de gran apertura. En este capítulo, los principales campos de aplicación son descritos y además se establece la necesidad de compensar retardos en subbandas. La teoría de bancos de filtros se expone en el capítulo 2; se selecciona y simula un banco de filtros modulado uniformemente con fase lineal. Las propiedades de convergencia de varios filtros adaptativos se muestran en el capítulo 4. Y finalmente, las técnicas de estimación de retardo son estudiadas y resumidas en el capítulo 5. Desde el punto de vista matemático, las principales contribución de esta disertación han sido: • Sección 3.1.4. Cálculo de la desviación de haz de un conformador de haz con compensación de retardo en pasos discretos en frecuencia intermedia. • Sección 3.2. Modelo matemático de un conformador de haz en subbandas. • Sección 3.2.2. Cálculo de la desviación de haz de un conformador de haz en subbandas con un buffer de retardo grueso. • Sección 3.2.4. Análisis de la influencia de los alias internos en la compensación en subbandas de retardo y fase. • Sección 3.2.4.2. Cálculo de la desviación de haz de un conformador de haz con compensación de retardo en subbandas. • Sección 3.2.6. Cálculo de la ganancia de relación señal a ruido de la agrupación de antenas en cada una de las subbandas. • Sección 3.3.2. Modelado de la función de transferencia de la agrupación de antenas bajo errores de estimación de retardo. • Sección 3.3.3. Modelado de los efectos de derivas de fase y retardo entre actualizaciones de las estimaciones. • Sección 3.4. Cálculo de la directividad de la agrupación de antenas con y sin compensación de retardos en subbandas. • Sección 5.2.6. Desarrollo de un algorimo para estimar la fase y el retardo entre dos señales a partir de su descomposición de subbandas bajo entornos estacionarios. • Sección 5.5.1. Desarrollo de un algorimo para estimar la fase, el retardo y la deriva de retardo entre dos señales a partir de su descomposición de subbandas bajo entornos no estacionarios. Las aplicaciones que se pueden beneficiar de estas técnicas son descritas en el capítulo 7: • Sección 6.2. Agrupaciones de antenas para comunicaciones de Espacio Profundo con capacidad multihaz y sin requisitos de calibración geométrica o de retardo de grupo. • Sección 6.2.6. Combinación en banda ancha de antenas con separaciones de miles de kilómetros, para recepción de sondas de espacio profundo. • Secciones 6.4 and 6.3. Combinación de estaciones remotas en banda Ka en escenarios de diversidad espacial, para recepción de satélites LEO o GEO. • Sección 6.3. Recepción de satélites GEO colocados con arrays de antenas multihaz. Las publicaciones a las que ha dado lugar esta tesis son las siguientes • A. Torre. Wideband antenna arraying over long distances. Interplanetary Progress Report, 42-194:1–18, 2013. En esta pulicación se resumen los resultados de las secciones 3.2, 3.2.2, 3.3.2, los algoritmos en las secciones 5.2.6, 5.5.1 y la aplicación destacada en 6.2.6. • A. Torre. Reception of wideband signals from geostationary collocated satellites with antenna arrays. IET Communications, Vol. 8, Issue 13:2229–2237, September, 2014. En esta segunda se muestran los resultados de la sección 3.2.4, el algoritmo en la sección 5.2.6.1 , y la aplicación mostrada en 6.3. ABSTRACT This dissertation is an attempt to solve some of the problems found nowadays in the reception of satellite signals under two particular challenging scenarios: Deep Space and Ka-band communications. Deep Space communications require from larger apertures on ground in order to increase the data rate. The option of using single dishes with diameters larger than 35 meters has severe drawbacks. Such antennas are expensive to maintain, prone to long downtimes, difficult to point and have a degraded performance in high frequency bands. The array solution, either with 12 meter or 35 meter antennas is deemed to be the most economically and technically feasible solution. Ka-band communications can also benefit from antenna arraying technology. The smaller aperture antennas that make up the array are easier to point and have a wider field of view allowing multiple simultaneous beams. Besides, site diversity techniques can be replaced by pure combination in order to increase link margin. Combination of far away antennas over a large bandwidth, either because a wideband signal or multiple narrowband signals are received, is a demanding task. This dissertation will show that the use of frequency domain beamformers with subband delay compensation can help to ease calibration requirements and, at the same time, provide with a wider field of view and enhanced equalization capabilities. In order to do so, the work has been focused on three main aspects. The first one is the bibliographic research of previous work on this subject. The second one is the mathematical modeling of the array combination process and the development of new phase/delay estimation algorithms. And the third one is the proposal of new applications in which these techniques can be used. Bibliographic research is mainly done in chapters 1, 2, 4 and 5. Chapter 1 gives a brief introduction to previous work in the field of large aperture antenna arraying. In this chapter, the main fields of application are described and the need for subband delay compensation is established. Filter bank theory is shown in chapter 2; a linear phase uniform modulated filter bank is selected and simulated under diverse conditions. The convergence properties of several adaptive filters are shown in chapter 4. Finally, delay estimation techniques are studied and summarized in chapter 5. From a mathematical point of view, the main contributions of this dissertation have been: • Section 3.1.4. Calculation of beam squint of an IF beamformer with delay compensation at discrete time steps. • Section 3.2. Establishment of a mathematical model of a subband beamformer. • Section 3.2.2. Calculation of beam squint in a subband beamformer with a coarse delay buffer. • Section 3.2.4. Analysis of the influence of internal aliasing on phase and delay subband compensation. • Section 3.2.4.2. Calculation of beam squint of a beamformer with subband delay compensation. • Section 3.2.6. Calculation of the array SNR gain at each of the subbands. • Section 3.3.2. Modeling of the transfer function of an array subject to delay estimation errors. • Section 3.3.3. Modeling of the effects of phase and delay drifts between estimation updates. • Section 3.4. Calculation of array directivity with and without subband delay compensation. • Section 5.2.6. Development of an algorithm to estimate relative delay and phase between two signals from their subband decomposition in stationary environments. • Section 5.5.1. Development of an algorithm to estimate relative delay rate, delay and phase between two signals from their subband decomposition in non stationary environments. The applications that can benefit from these techniques are described in chapter 7: • Section 6.2. Arrays of antennas for Deep Space communications with multibeam capacity and without geometric or group delay calibration requirement. • Section 6.2.6. Wideband antenna arraying over long distances, in the range of thousands of kilometers, for reception of Deep Space probes. • Sections 6.4 y 6.3. Combination of remote stations in Ka-band site diversity scenarios for reception of LEO or GEO satellites. • Section 6.3. Reception of GEO collocated satellites with multibeam antenna arrays. The publications that have been made from the work in this dissertation are • A. Torre. Wideband antenna arraying over long distances. Interplanetary Progress Report, 42-194:1–18, 2013. This article shows the results in sections 3.2, 3.2.2, 3.3.2, the algorithms in sections 5.2.6, 5.5.1 and the application in section 6.2.6. • A. Torre. Reception of wideband signals from geostationary collocated satellites with antenna arrays. IET Communications, Vol. 8, Issue 13:2229–2237, September, 2014. This second article shows among others the results in section 3.2.4, the algorithm in section 5.2.6.1 , and the application in section 6.3.