Inventi Impact - Signal Processing
Current Issue : April - June 2019
Volume : 2019
Issue Number : 2
Articles : 5 Articles
Articles
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Inventi:esp/28471/19
A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial BeeColony Algorithm
For the purpose of reducing noise from grain flow signal, this paper proposes a filtering method that is on the basis of empirical mode decomposition (EMD) and artificial bee colony (ABC) algorithm. At first, decomposing noise signal is performed adaptively into intrinsic mode functions (IMFs). Then....
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Inventi:esp/28472/19
Classification of Heart Sound Signal Using Multiple Features
Cardiac disorders are critical and must be diagnosed in the early stage using routine auscultation examination with high precision. Cardiac auscultation is a technique to analyze and listen to heart sound using electronic stethoscope, an electronic stethoscope is a device which provides the digital ....
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Inventi:esp/28473/19
A Matlab/Simulink Development and Verification Platform for a Frequency Estimation System
The precise estimation of the frequency of the signal is of great significance in the Radar system, the electronic warfare system and many other systems. In this paper, we propose a development and verification platform for the frequency estimation system in the Matlab and Simulink environment. Its ....
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Inventi:esp/28474/19
Low-Cost Posture Recognition of Moving Hands by Profile-Mold Construction in Cluttered Background and Occlusion
In this paper, we propose a low-cost posture recognition scheme using a single webcam for the signaling hand with nature sways and possible occlusions. It goes for developing the untouchable low-complexity utility based on friendly hand-posture signaling. The scheme integrates the dominant temporal-....
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Inventi:esp/28475/19
Iss2Image: A Novel Signal-Encoding Technique for CNN-Based Human Activity Recognition
The most significant barrier to success in human activity recognition is extracting and selecting the right features. In traditional methods, the features are chosen by humans, which requires the user to have expert knowledge or to do a large amount of empirical study. Newly developed deep learning ....
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