Variable Star Signature Classification using Slotted Symbolic Markov Modeling
نویسندگان
چکیده
منابع مشابه
Prosody-Dependent Acoustic Modeling Using Variable-Parameter Hidden Markov Models
As an effort to make prosody useful in spontaneous speech recognition, we adopt a quasi-continuous prosodic annotation and accordingly design a prosody-dependent acoustic model to improve ASR performances. We propose a variable-parameter Hidden Markov Models, modeling the mean vector as a function of the prosody variable through a polynomial regression model. The prosodically-adapted acoustic m...
متن کاملAlgorithms for variable length Markov chain modeling
UNLABELLED We present a general purpose implementation of variable length Markov models. Contrary to fixed order Markov models, these models are not restricted to a predefined uniform depth. Rather, by examining the training data, a model is constructed that fits higher order Markov dependencies where such contexts exist, while using lower order Markov dependencies elsewhere. As both theoretica...
متن کاملAccelerometry-Based Classification of Human Activities Using Markov Modeling
Accelerometers are a popular choice as body-motion sensors: the reason is partly in their capability of extracting information that is useful for automatically inferring the physical activity in which the human subject is involved, beside their role in feeding biomechanical parameters estimators. Automatic classification of human physical activities is highly attractive for pervasive computing ...
متن کاملMalware Detection using Classification of Variable-Length Sequences
In this paper, a novel method based on the graph is proposed to classify the sequence of variable length as feature extraction. The proposed method overcomes the problems of the traditional graph with variable length of data, without fixing length of sequences, by determining the most frequent instructions and insertion the rest of instructions on the set of “other”, save speed and memory. Acco...
متن کاملA New On-Line Signature Verification Algorithm Using Variable Length Segmentation and Hidden Markov Models
In this paper, a new on-line handwritten signature verification system using Hidden Markov Model (HMM) is presented. The proposed system segments each signature based on its perceptually important points and then computes for each segment a number of features that are scale and displacement invariant. The resulted sequence is then used for training an HMM to achieve signature verification. Our ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: New Astronomy
سال: 2017
ISSN: 1384-1076
DOI: 10.1016/j.newast.2016.06.001