Efficient time-series analysis can impact multiple application domains such as motif discovery in gene analysis or music data, extracting spectro-temporal patterns in acoustic scene analysis, or annotating and classifying electrical bio-signals (such as ECG, EEG, and EMG) for medical applications.
Time-series analysis involves a variety of tasks.
To predict future...
The study evaluates performances of three multiple time series
(MTS) forecasting methods; investigates possible improvements in
MTS forecasting operations, and proposes a multiple time series
based forecasting system. Time series considered are finite,
linear, covariance stationary, and discrete.
Specific objectives for the thesis were: (a) conducting comparative
studies of MTS...
Finite order autoregressive models for time series are often
used for prediction and other inferences. Given the order of the
model, the parameters of the models can be estimated by least
squares, maximum likelihood, or the Yule-Walker method. The
basic problem is estimating the order of the model. A number...
In engineering, biology, ecology, medicine, economics and social
science, some processes are essentially bilinear, and some could be
approximated accurately by bilinear processes under certain conditions.
In this thesis the bilinear stochastic process and bilinear time series
are discussed.
Bilinear models essentially are nonlinear; the superposition rule
is not valid....
We consider two semiparametric regression models for data analysis, the stochastic additive model (SAM) for nonlinear time series data and the additive coefficient model (ACM) for randomly sampled data with nonparametric structure. We employ the SCAD-penalized polynomial spline estimation method for estimation and simultaneous variable selection in both models. It...
The use of Landsat data has historically been constrained to spectral and spatial information derived from a carefully selected image or set of images. However, free and open access to Landsat imagery combined with advances in data storage and computing are revolutionizing how the Landsat temporal domain is used to...
Physical activity recognition using accelerometer data is a rapidly emerging field with many real-world applications. Much of the previous work in this area has assumed that the accelerometer data has already been segmented into pure activities, and the activity recognition task has been to classify these segments. In reality, activity...
The purpose of this study is to develop experimental techniques to
characterize typical interconnect discontinuities, including bends, steps, T
junctions, vias and pads, which are the most commonly encountered
interconnections in high speed digital integrated circuits, hybrid and
monolithic microwave circuits and electronic packages. The time domain
reflection response of...
A new second order accurate nonuniform grid spacing technique which does not
depend on supraconvergence is developed for Finite Difference Time Domain (FDTD)
simulation of general three dimensional structures. The technique is useful for FDTD
simulations of systems which require finer details in small regions of the simulation space by...