Sökning: "non-stationary random processes"
Visar resultat 1 - 5 av 6 avhandlingar innehållade orden non-stationary random processes.
1. Ambiguity Domain Definitions and Covariance Function Estimation for Non-Stationary Random Processes in Discrete Time
Sammanfattning : The ambiguity domain plays a central role in estimating the time-varying spectrum of a non-stationary random process in continuous time, since multiplication in this domain is equivalent with estimating the covariance function of the random process using an intuitively appealing estimator. For processes in discrete time there exists a corresponding covariance function estimator. LÄS MER
2. Discrete Stochastic Time-Frequency Analysis and Cepstrum Estimation
Sammanfattning : The theory of stochastic time-frequency analysis of non-stationary random processes has mostly been developed for processes in continuous time. In practice however, random processes are observed, processed, and interpreted at a finite set of time points. LÄS MER
3. Crossings and maxima in Gaussian fields and seas
Sammanfattning : In this thesis the focus is on crossing points in random fields and the probability distributions of various crossing variables in different applications. The crossing points are generalisations to random fields of points of level crossings by stochastic processes. LÄS MER
4. Radio Channel Prediction Based on Parametric Modeling
Sammanfattning : Long range channel prediction is a crucial technology for future wireless communications. The prediction of Rayleigh fading channels is studied in the frame of parametric modeling in this thesis.Suggested by the Jakes model for Rayleigh fading channels,deterministic sinusoidal models were adopted for long rangechannel prediction in early works. LÄS MER
5. Stochastic modelling and analysis of early mouse development
Sammanfattning : The aim of this thesis is to model and describe dynamical events for biological cells using statistical and mathematical tools. The thesis includes five papers that all relate to stochastic modelling of cells. LÄS MER
