965 resultados para Signal processing - Mathematical models


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A recent study of a pair of sympatric species of cichlids in Lake Apoyo in Nicaragua is viewed as providing probably one of the most convincing examples of sympatric speciation to date. Here, we describe and study a stochastic, individual-based, explicit genetic model tailored for this cichlid system. Our results show that relatively rapid (<20,000 generations) colonization of a new ecological niche and (sympatric or parapatric) speciation via local adaptation and divergence in habitat and mating preferences are theoretically plausible if: (i) the number of loci underlying the traits controlling local adaptation, and habitat and mating preferences is small; (ii) the strength of selection for local adaptation is intermediate; (iii) the carrying capacity of the population is intermediate; and (iv) the effects of the loci influencing nonrandom mating are strong. We discuss patterns and timescales of ecological speciation identified by our model, and we highlight important parameters and features that need to be studied empirically to provide information that can be used to improve the biological realism and power of mathematical models of ecological speciation.

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In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This workexplores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three different strategies to detect tonic, namely, the concert method, the template matching and segmented histogram method are proposed. The concert method exploits the fact that the tonic is constant over a piece/concert.templatematchingmethod and segmented histogrammethodsuse the properties: (i) the tonic is always present in the background, (ii) some notes are less inflected and dominant, to detect the tonic of individual pieces. All the three methods yield good results for Carnatic music (90−100% accuracy), while for Hindustanimusic, the templatemethod works best, provided the v¯adi samv¯adi notes for a given piece are known (85%).

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A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.

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Neural signal processing is a discipline within neuroengineering. This interdisciplinary approach combines principles from machine learning, signal processing theory, and computational neuroscience applied to problems in basic and clinical neuroscience. The ultimate goal of neuroengineering is a technological revolution, where machines would interact in real time with the brain. Machines and brains could interface, enabling normal function in cases of injury or disease, brain monitoring, and/or medical rehabilitation of brain disorders. Much current research in neuroengineering is focused on understanding the coding and processing of information in the sensory and motor systems, quantifying how this processing is altered in the pathological state, and how it can be manipulated through interactions with artificial devices including brain–computer interfaces and neuroprosthetics.

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Preference relations, and their modeling, have played a crucial role in both social sciences and applied mathematics. A special category of preference relations is represented by cardinal preference relations, which are nothing other than relations which can also take into account the degree of relation. Preference relations play a pivotal role in most of multi criteria decision making methods and in the operational research. This thesis aims at showing some recent advances in their methodology. Actually, there are a number of open issues in this field and the contributions presented in this thesis can be grouped accordingly. The first issue regards the estimation of a weight vector given a preference relation. A new and efficient algorithm for estimating the priority vector of a reciprocal relation, i.e. a special type of preference relation, is going to be presented. The same section contains the proof that twenty methods already proposed in literature lead to unsatisfactory results as they employ a conflicting constraint in their optimization model. The second area of interest concerns consistency evaluation and it is possibly the kernel of the thesis. This thesis contains the proofs that some indices are equivalent and that therefore, some seemingly different formulae, end up leading to the very same result. Moreover, some numerical simulations are presented. The section ends with some consideration of a new method for fairly evaluating consistency. The third matter regards incomplete relations and how to estimate missing comparisons. This section reports a numerical study of the methods already proposed in literature and analyzes their behavior in different situations. The fourth, and last, topic, proposes a way to deal with group decision making by means of connecting preference relations with social network analysis.

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The present study aimed to determine the volumetric shrinkage rate of bean (Phaseolus vulgaris L.) seeds during air-drying under different conditions of air, temperature and relative humidity, and to adjust several mathematical models to the empiric values observed, and select the one that best represents the phenomenon. Six mathematical models were adjusted to the experimental values to represent the phenomenon. It was determined the degree of adjustment of each model from the value of the coefficient of determination, the behavior of the distribution of the residuals, and the magnitude of the average relative and estimated errors. The rate of volumetric shrinkage that occurred in bean seeds during drying is between 25 and 37%. It basically depends on the final moisture content, regardless of the air conditions during drying. The Modified Bala & Woods' model best represented the process.

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Solid mixtures for refreshment are already totally integrated to the Brazilian consumers' daily routine, because of their quick preparation method, yield and reasonable price - quite lower if compared to 'ready-to-drink' products or products for prompt consumption, what makes them economically more accessible to low-income populations. Within such a context, the aim of this work was to evaluate the physicochemical and mineral composition, as well as the hygroscopic behavior of four different brands of solid mixture for mango refreshment. The BET, GAB, Oswim and Henderson mathematical models were built through the adjustment of experimental data to the isotherms of adsorption. Results from the physiochemical evaluation showed that the solid mixtures for refreshments are considerable sources of ascorbic acid and reductor sugar; and regarding mineral compounds, they are significant sources of calcium, sodium and potassium. It was also verified that the solid mixtures for refreshments of the four studied brands are considered highly hygroscopic.

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Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

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Surface (Lambertain) color is a useful visual cue for analyzing material composition of scenes. This thesis adopts a signal processing approach to color vision. It represents color images as fields of 3D vectors, from which we extract region and boundary information. The first problem we face is one of secondary imaging effects that makes image color different from surface color. We demonstrate a simple but effective polarization based technique that corrects for these effects. We then propose a systematic approach of scalarizing color, that allows us to augment classical image processing tools and concepts for multi-dimensional color signals.

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Resumen basado en el de la publicaci??n

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The main objective of this thesis was the integration of microstructure information in synoptic descriptors of turbulence, that reflects the mixing processes. Turbulent patches are intermittent in space and time, but they represent the dominant process for mixing. In this work, the properties of turbulent patches were considered the potential input for integrating the physical microscale measurements. The development of a method for integrating the properties of the turbulent patches required solving three main questions: a) how can we detect the turbulent patches from he microstructure measurements?; b) which are the most relevant properties of the turbulent patches?; and ) once an interval of time has been selected, what kind of synoptic parameters could better reflect the occurrence and properties of the turbulent patches? The answers to these questions were the final specific objectives of this thesis.

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The purpose of this study was to examine objective and subjective distortion present when frequency modulation (FM) systems were coupled with four digital signal processing (DSP) hearing aids. Electroacoustic analysis and subjective listening tests by experienced audiologists revealed that distortion levels varied across hearing aids and channels.

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This paper reviews a study to determine the usefulness of signal processing along with lipreading in improving speech perception of profoundly hearing impaired persons.