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Lee, Jae Han,
Wireless sensor networks (WSNs) have received huge attention during the recent years due to their applications in a large number of areas such as environmental monitoring, health and traffic monitorin...
complete descriptionhttp://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8318
Kim, Sanggyun, Yoo, Chang D.,
This paper considers the problem of blindly separating sub- and super-Gaussian sources from underdetermined mixtures. The underlying sources are assumed to be composed of two orthogonal components: on...
complete descriptionhttp://hdl.handle.net/1721.1/51862
Hao, Jiucang,
Statistical signal processing has been very successful. We proposed novel probabilistic models and developed efficient algorithms for two important problems: speech enhancement and source separation. ...
complete descriptionhttp://www.escholarship.org/uc/item/7852b720
Ma, Hui,
Target tracking is one of the typical applications of wireless sensor networks: a large number of spatially deployed sensor nodes collaboratively sense, process and estimate the target state (e.g., po...
complete descriptionhttp://hdl.handle.net/2440/49462
Jebara, Tony (Tony S.), 1974-,
I propose a common framework that combines three different paradigms in machine learning: generative, discriminative and imitative learning. A generative probabilistic distribution is a principled way...
complete descriptionhttp://hdl.handle.net/1721.1/8323
Hao, Jiangang,
Galaxy clusters can be used as a sensitive probe for cosmology. A large cluster catalog that extends to high redshift with well measured masses is indispensable for precisely constraining cosmological...
complete descriptionhttp://hdl.handle.net/2027.42/63840
Xu, Lei,
The aim of this dissertation is to develop spatial models for multi-subject fMRI data. While there has been much work on univariate modeling of each voxel for single- and multi-subject data, and some ...
complete descriptionhttp://hdl.handle.net/2027.42/57656
María Luisa Ávila-Jiménez Stephen James Coulson,
We aimed to describe the main Arctic biogeographical patterns of the Collembola, and analyze historical factors and current climatic regimes determining Arctic collembolan species distribution. Furthe...
complete descriptionhttp://www.mdpi.com/2075-4450/2/3/273/
Zhang, Yaodong, S. M. Massachusetts Institute of Technology,
The problem of keyword spotting in audio data has been explored for many years. Typically researchers use supervised methods to train statistical models to detect keyword instances. However, such supe...
complete descriptionhttp://hdl.handle.net/1721.1/54655
Chen, Minhua,
The concept of sparseness is harnessed to learn a low dimensional representation of high dimensional data. This sparseness assumption is exploited in multiple ways. In the Bayesian Elastic Net, a s...
complete descriptionhttp://hdl.handle.net/10161/5588