In Computer Vision, two-dimensional shape classifcation is a complex and well studied topic, often basic for three-dimensional object recognition. Object contours are a widely cho...
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
Wavelet-domain hidden Markov models (HMMs) have been recently proposed and applied to image processing, e.g., image denoising. In this paper, we develop a new HMM, called local co...
We define the crouching Dirichlet, hidden Markov model (CDHMM), an HMM for partof-speech tagging which draws state prior distributions for each local document context. This simple...
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...