scholarly journals Online map-matching based on Hidden Markov model for real-time traffic sensing applications

2012 ◽  
Author(s):  
C.Y. Goh ◽  
J. Dauwels ◽  
N. Mitrovic ◽  
M. T. Asif ◽  
A. Oran ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Real Time ◽  
Hidden Markov ◽  
Map Matching ◽  
Real Time Traffic ◽  
Sensing Applications

A Low-power Real-time Hidden Markov Model Accelerator for Gesture User Interface on Wearable Devices

2019 ◽  
Vol 19 (4) ◽  
pp. 396-403 ◽  
Author(s):  
Hyeon-Gu Do ◽  
Seongrim Choi ◽  
Jaemin Hwang ◽  
Ara Kim ◽  
Byeong-Gyu Nam
Keyword(s):  
User Interface ◽  
Markov Model ◽  
Low Power ◽  
Hidden Markov Model ◽  
Real Time ◽  
Hidden Markov ◽  
Wearable Devices

Real Time Intrusion Prediction based on Optimized Alerts with Hidden Markov Model

2012 ◽  
Vol 7 (2) ◽  
Author(s):  
Alireza Shameli Sendi ◽  
Michel Dagenais ◽  
Masoume Jabbarifar ◽  
Mario Couture
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Real Time ◽  
Hidden Markov

Speech Silicon: An FPGA Architecture for Real-Time Hidden Markov-Model-Based Speech Recognition

2006 ◽  
Vol 2006 (1) ◽  
pp. 048085 ◽  
Author(s):  
Jeffrey Schuster ◽  
Kshitij Gupta ◽  
Raymond Hoare ◽  
AlexK Jones
Keyword(s):  
Speech Recognition ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Real Time ◽  
Hidden Markov ◽  
Model Based ◽  
Fpga Architecture

Quality Control of Information Engineering Surveillance Based on Baum-Welch Algorithm

2011 ◽  
Vol 63-64 ◽  
pp. 178-181
Author(s):  
Hong Zhi Liu ◽  
Li Gao
Keyword(s):  
Quality Control ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Random Process ◽  
Real Time ◽  
Software Quality ◽  
Hidden Markov ◽  
Proposed Model ◽  
Information Engineering ◽  
Five Elements

A new method of Quality Control for Information Engineering Surveillance based on Hidden Markov Model (HMM) has been proposed and the related model been built by us. The process of information engineering quality surveillance can be seen as a two-layered random process. The five elements of HMM correspond with the process of quality surveillance through abstracting the characteristics of the surveillance process. Software quality can be estimated under the model. In this paper, we divided the five elements. Therefore, the model was improved from single dimension to multi-dimension, trained by Baum-Welch algorithm. Experimental results show that the proposed model proves to be feasible and real-time when it is used for quality control.

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