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Number of results: 4
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Abstract

A trellis coded 4-ary Pulse Amplitude Modulation (4-PAM) is presented, where the encoding algorithm is derived from Distance Preserving Mapping (DPM) algorithm. In this work, we modify the DPM algorithm for 4-PAM and obtain a new construction for mapping binary sequences to permutation sequences, where the permutation sequences are obtained by permuting symbols of a 4-PAM constellation. The resulting codebook of permutation sequences formed this way are termed mappings. We also present several metrics for assessing the performance of the mappings from our construction, and we show that a metric called the Sum of Product of Distances (SOPD) is the best metric to use when judging the performance of the mappings. Finally, performance results are presented, where the mappings from our construction are compared against each other and also against the conventional mappings in the literature.

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Authors and Affiliations

Thokozani Shongwe
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Abstract

The aim of this paper is to compare the efficiency of various outlier correction methods for ECG signal processing in biometric applications. The main idea is to correct anomalies in various segments of ECG waveform rather than skipping a corrupted ECG heartbeat in order to achieve better statistics. Experiments were performed using a self-collected Lviv Biometric Dataset. This database contains over 1400 records for 95 unique persons. The baseline identification accuracy without any correction is around 86%. After applying the outlier correction the results were improved up to 98% for autoencoder based algorithms and up to 97.1% for sliding Euclidean window. Adding outlier correction stage in the biometric identification process results in increased processing time (up to 20%), however, it is not critical in the most use-cases.

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Authors and Affiliations

Su Jun
Miroslaw Szmajda
Volodymyr Khoma
Yuriy Khoma
Dmytro Sabodashko
Orest Kochan
Jinfei Wang
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Abstract

The copy-move forgery detection (CMFD) begins with the preprocessing until the image is ready to process. Then, the image features are extracted using a feature-transform-based extraction called the scale-invariant feature transform (SIFT). The last step is features matching using Generalized 2 Nearest- Neighbor (G2NN) method with threshold values variation. The problem is what is the optimal threshold value and number of keypoints so that copy-move detection has the highest accuracy. The optimal threshold value and number of keypoints had determined so that the detection has the highest accuracy. The research was carried out on images without noise and with Gaussian noise.

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Authors and Affiliations

R. Rizal Isnanto
Ajub Ajulian Zahra
Imam Santoso
Muhammad Salman Lubis
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Abstract

The artificial bee colony (ABC) intelligence algorithm is widely applied to solve multi-variable function optimization problems. In order to accurately identify the parameters of the surface-mounted permanent magnet synchronous motor (SPMSM), this paper proposes an improved ABC optimization method based on vector control to solve the multi-parameter identification problem of the PMSM. Because of the shortcomings of the existing parameter identification algorithms, such as high computational complexity and data saturation, the ABC algorithm is applied for the multi-parameter identification of the PMSM for the first time. In order to further improve the search speed of the ABC algorithm and avoid falling into the local optimum, Euclidean distance is introduced into the ABC algorithm to search more efficiently in the feasible region. Applying the improved algorithm to multi-parameter identification of the PMSM, this method only needs to sample the stator current and voltage signals of the motor. Combined with the fitness function, the online identification of the PMSM can be achieved. The simulation and experimental results show that the ABC algorithm can quickly identify the motor stator resistance, inductance and flux linkage. In addition, the ABC algorithm improved by Euclidean distance has faster convergence speed and smaller steady-state error for the identification results of stator resistance, inductance and flux linkage.
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Bibliography

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Authors and Affiliations

Chunli Wu
1
ORCID: ORCID
Shuai Jiang
1
Chunyuan Bian
1

  1. College of Information Science and Engineering, Northeastern University, China

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