Results 31 to 40 of about 241,041 (317)
Hidden Markov Model Based on Logistic Regression
Mathematics, 2023 A hidden Markov model (HMM) is a useful tool for modeling dependent heterogeneous phenomena. It can be used to find factors that affect real-world events, even when those factors cannot be directly observed.
Byeongheon Lee, Joowon Park, Yongku Kim
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Prediksi Kurs Rupiah Terhadap Dolar Dengan FTS-Markov Chain Dan Hidden Markov Model
Jurnal Derivat, 2019 Hidden Markov model is a development of the Markov chain where the state cannot be observed directly (hidden), but can only be observed, a set of other observations and combination of fuzzy logic and Markov chain to predict Rupiah exchange rate against ...
Maria Titah Jatipaningrum +2 more
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Dirichlet Process Hidden Markov Multiple Change-point Model [PDF]
, 2014 This paper proposes a new Bayesian multiple change-point model which is based on the hidden Markov approach. The Dirichlet process hidden Markov model does not require the specification of the number of change-points a priori.
Chong, Terence T. L. +2 more
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Hidden Markov Model for Stock Selection
Risks, 2015 The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market ...
Nguyet Nguyen, Dung Nguyen
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Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space
Advanced Robotics Research, EarlyView.A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo +6 more
wiley +1 more source
Advanced Robotics Research, EarlyView.Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
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Feedforward Factorial Hidden Markov Model
MathematicsThis paper introduces a novel kind of factorial hidden Markov model (FHMM), specifically the feedforward FHMM (FFHMM). In contrast to traditional FHMMs, the FFHMM is capable of directly utilizing supplementary information from observations through ...
Zhongxing Peng, Wei Huang, Yinghui Zhu
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International Journal of Advanced Robotic Systems, 2019 Robot introspection aids robots to understand what they do and how they do it. Previous robot introspection techniques have often used parametric hidden Markov models or supervised learning techniques, implying that the number of hidden states or classes
Hongmin Wu, Yisheng Guan, Juan Rojas
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Global Stock Selection with Hidden Markov Model
Risks, 2020 Hidden Markov model (HMM) is a powerful machine-learning method for data regime detection, especially time series data. In this paper, we establish a multi-step procedure for using HMM to select stocks from the global stock market.
Nguyet Nguyen, Dung Nguyen
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Pendugaan Parameter Model Hidden Markov * [PDF]
, 2005 Pendugaan parameter untuk model Hidden Markov Elliott et. al. (1995) dilakukan mengunakan Metode Maximum Likelihood dan pendugaan ulang menggunakan metode Expectation Maximization yang melibatkan Perubahan ukuran. Dari metode tersebut diperoleh algoritma
KRISTINA, L. (L), SETIAWATY, B. (B)
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