Progressive Bounded Error Piecewise Linear Approximation with Resolution Reduction for Time Series Data Compression by Jeng-Wei Lin, Shih-wei Liao, Yu-Hung Tsai, Ching-Che Huang

Get full text

Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals by Ahmed Shaheen, Liang Ye, Chrishni Karunaratne, Tapio Seppänen

“…The FGDAE showed the best performance on all seven error metrics used in our work in different noise intensities and artifact combinations compared with state-of-the-art algorithms. …”
Get full text

Variational AutoEncoder for synthetic insurance data by Charlotte Jamotton, Donatien Hainaut

“…This study introduces novel insights into utilising VAEs for unsupervised learning tasks in actuarial science, including dimension reduction and synthetic data generation. We propose a VAE model with a quantile transformation for continuous (latent) variables, a reconstruction loss that combines categorical cross-entropy and mean squared error, and a KL divergence-based regularisation term. …”
Get full text

Optimizing low complexity encoding method for systematic polar code by Linhua MA, Shiping LIU, Xing HU, Tianyu HUANG, Bin XU

Get full text

ANALYSIS OF STUDENTS’ ERRORS WITH NEWMAN'S ERROR ANALYSIS ON VIBRATION, WAVES AND SOUNDS CONCEPT by Prita Dwi Nurlaeli, Arif Widiyatmoko

“…Question number four reading error 0%, comprehension error 33.33% transformation error 19.04%, process skills error and encoding error is 0%. …”
Get full text

TYPE OF ERROR IN COMPLETING MATHEMATICAL PROBLEM BASED ON NEWMAN’S ERROR ANALYSIS (NEA) AND POLYA THEORY by Widodo Winarso, Sirojudin Wahid, Rizkiah Rizkiah

“…The study results based on Newman's Error Analysis are errors reading by 1%, error understanding by 0%, error transforms by 3%, error processing ability by 5%, and error encoding by 7%. …”
Get full text

Effects of aging on word position encoding in Chinese reading by Zhiwei Liu, Yan Li, Jingxin Wang

“…This study examined age-related differences in the flexibility of word position encoding by investigating the transposed-word effect in young and older adults. …”
Get full text

Achieving Computational Gains with Quantum Error-Correction Primitives: Generation of Long-Range Entanglement Enhanced by Error Detection by Haoran Liao, Gavin S. Hartnett, Ashish Kakkar, Adrian Tan, Michael Hush, Pranav S. Mundada, Michael J. Biercuk, Yuval Baum

“…In this paper, we demonstrate that the strategic application of QEC primitives without logical encoding can yield significant advantages on superconducting processors—relative to any alternative error-reduction strategy—while only requiring a modest overhead. …”
Get full text

Achieving Computational Gains with Quantum Error-Correction Primitives: Generation of Long-Range Entanglement Enhanced by Error Detection by Haoran Liao, Gavin S. Hartnett, Ashish Kakkar, Adrian Tan, Michael Hush, Pranav S. Mundada, Michael J. Biercuk, Yuval Baum

“…In this paper, we demonstrate that the strategic application of QEC primitives without logical encoding can yield significant advantages on superconducting processors—relative to any alternative error-reduction strategy—while only requiring a modest overhead. …”
Get full text

Any-to-any voice conversion using representation separation auto-encoder by Zhihua JIAN, Zixu ZHANG

“…In view of the problem that it was difficult to separate speaker personality characteristics from semantic content information in any-to-any voice conversion under non-parallel corpus, which led to unsatisfied performance, a voice conversion method, called RSAE-VC (representation separation auto-encoder voice conversion) was proposed.The speaker’s personality characteristics in the speech were regarded as time invariant and the content information as time variant, and the instance normalization and activation guidance layer were used in the encoder to separate them from each other.Then the content information of the source speech and the personality characteristics of the target one was utilized to synthesize the converted speech by the decoder.The experimental results demonstrate that RSAE-VC has an average reduction of 3.11% and 2.41% in Mel cepstral distance and root mean square error of pitch frequency respectively, and has an increasement of 5.22% in MOS and 8.45% in ABX, compared with the AGAIN-VC (activation guidance and adaptive instance normalization voice conversion) method.In RSAE-VC, self-content loss is applied to make the converted speech reserve more content information, and self-speaker loss is used to separate the speaker personality characteristics from the speech better, which ensure the speaker personality characteristics be left in the content information as little as possible, and the conversion performance is improved.…”
Get full text

Design of Radix-8 Unsigned Bit Pair Recoding Algorithm-Based Floating-Point Multiplier for Neural Network Computations by J. Jean Jenifer Nesam, S. Sankar Ganesh

“…The partial product rows are reduced from n to <inline-formula> <tex-math notation="LaTeX">$\frac {n}{4}$ </tex-math></inline-formula> for <inline-formula> <tex-math notation="LaTeX">$n\times n$ </tex-math></inline-formula> binary multiplier using the BPR algorithm with parallel processed partial product reduction. The new algorithm performs partial product row reduction without the 2&#x2019;s complement, Negative Encoding (NE), and Sign Extension (SE) are required for Booth recoded-based multiplication but these computations are not required for floating point unsigned multiplication. …”
Get full text

Research on multi-scenario adaptive acoustic encoders based on neural architecture search by Yiliang Wu, Yiliang Wu, Xuliang Luo, Xuliang Luo, Fengchan Guo, Tinghui Lu, Tinghui Lu, Cuimei Liu

“…The SAAE method achieves an average error rate reduction of more than 5% compared with existing acoustic encoders, highlighting its capability to deeply analyze speech features in specific scenarios and design high-performance acoustic encoders in a targeted manner.…”
Get full text

Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…Unlike traditional CNN approaches, our method offers improved reliability by reducing time complexity, minimizing errors, and enhancing noise reduction. Leveraging a comprehensive dataset from KAGGLE containing 35,126 retinal fundus images representing one healthy (normal) stage and four DR stages, our proposed model demonstrates superior accuracy compared to existing deep learning algorithms. …”
Get full text

PEGASUS-XL with saliency-guided scoring and long-input encoding for multi-document abstractive summarization by Rawan Alsultan, Alaa Sagheer, Hala Hamdoun, Lamya Alshamlan, Latifah Alfadhli

“…Ablation studies quantify the contribution of each component, and detailed error analysis identifies remaining issues such as factual drift and residual redundancy. …”
Get full text

A proposed deep learning model for multichannel ECG noise reduction by Jay Prakash Maurya, Manish Manoria, Sunil Joshi

“…Comparison of ECG signal patterns is very difficult manually, and machine-based interpretation is a demand of society. Errors in ECG interpretation might result from noise contamination of ECG signals. …”
Get full text

Optimization Driven Variational Autoencoder GAN for Artifact Reduction in EEG Signals for Improved Neurological Disorder and Disability Assessment by Sikkandar Mohamed Yacin, Sabarunisha Begum S., Alassaf Ahmad, AlMohimeed Ibrahim, Alhussaini Khalid, Aleid Adham, Alhaidar Abdulrahman Khalid

Get full text

Truncation Artifact Reduction in Stationary Inverse-Geometry Digital Tomosynthesis Using Deep Convolutional Generative Adversarial Network by Burnyoung Kim, Seungwan Lee

“…The proposed network employed an encoder–decoder architecture for the generator, and a dilated convolution block was added between the encoder and decoder. …”
Get full text

PAPR Reduction in DCO-OFDM Visible Light Communication Systems Using Optimized Odd and Even Sequences Combination by Wei-Wen Hu

“…Even and odd sequences are obtained by adopting an inverse fast Fourier transform on the even and odd parts of a Hermitian symmetry encoded signal, respectively. Furthermore, a deterministic and efficient selection method of cyclic shift and phase rotation is derived to improve PAPR reduction performance and ensure that each candidate is unique, so that the receiver can recover the transmitted candidate signal without the use of SI. …”
Get full text

A Modified Selected Mapping Scheme for Peak-to-Average Power Ratio Reduction in Polar-Coded Orthogonal Frequency-Division Multiplexing Systems by Chao Xing, Nixi Chen Hu, Ana García Armada

“…Furthermore, for PC-SLM schemes employing the partially frozen bit method, the BP-GF-based receiver achieves a PAPR reduction and error correction performance comparable to that of the successive cancellation (SC)-based receiver. …”
Get full text

Generative autoencoder to prevent overregularization of variational autoencoder by YoungMin Ko, SunWoo Ko, YoungSoo Kim

Get full text