Scalable FPGA Implementation of a Reliability-Based Direct Turbo Decoder for Short Block Codes by Senthil Murugan, Ramesh Bhakthavatchalu, Karthi Balasubramanian, B. Yamuna, Deepak Mishra, Sree Ranjani Rajendran

“…Turbo codes are widely used in satellite and mobile communication systems for their strong error-correcting performance. However, conventional iterative decoders such as Log-MAP suffer from high complexity and exhibit error floors in short block-length regimes. …”
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Mapping Peatlands Combing Deep Learning With Sparse Spectral Unmixing Based on Zhuhai-1 Hyperspectral Images by Yulin Xu, Xiaodong Na

“…A multihead attention mechanism based on the transformer encoder captures global contextual information by correlating patches in the image, facilitating precise hyperspectral data reconstruction. …”
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Research on a PCA-transformer-based prediction algorithm for gas concentration in working face by YANG Jian, SHU Longyong, ZHANG Shulin, QIN Kai, CUI Cong

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Devaluing memories of reward: a case for dopamine by Benjamin R. Fry, Nicolette Russell, Victoria Fex, Bing Mo, Nathan Pence, Joseph A. Beatty, Fredric P. Manfredsson, Brandon A. Toth, Christian R. Burgess, Samuel Gershman, Alexander W. Johnson

“…Abstract Midbrain dopamine cells encode differences in predictive and expected value to support learning through reward prediction error. …”
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Classical and Quantum Algorithms for Characters of the Symmetric Group by Sergey Bravyi, David Gosset, Vojtech Havlicek, Louis Schatzki

“…To assess classical hardness of these problems, we present a general reduction from strong simulation (computing a given probability) to weak simulation (sampling with a small error). …”
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LPRLC: Linear predictive run length coding to improve energy consumption of wireless body area networks by Mahdieh Hajiloo Vakil, Zahra Shirmohammadi

“…First- Linear Predictive Coding (LPC) for data prediction, Second- Error calculation, Third- Error coding with Run Length Encoding (RLE) for data compression. …”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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Demonstration of Measurement-Enhanced State Preparation and Erasure Conversion in a Molecular Tweezer Array by Connor M. Holland, Yukai Lu, Samuel J. Li, Callum L. Welsh, Lawrence W. Cheuk

“…For these applications, the reduction and mitigation of errors remain major challenges. …”
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Smooth pursuit and visual occlusion: active inference and oculomotor control in schizophrenia. by Rick A Adams, Laurent U Perrinet, Karl Friston

“…Furthermore, we show that a single deficit in the postsynaptic gain of prediction error units (encoding the precision of posterior beliefs) can account for several features of smooth pursuit in schizophrenia: namely, a reduction in motor gain and anticipatory eye movements during visual occlusion, a paradoxical improvement in tracking unpredicted deviations from target trajectories and a failure to recognise and exploit regularities in the periodic motion of visual targets. …”
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ADEPNET: A Dynamic-Precision Efficient Posit Multiplier for Neural Networks by Aditya Anirudh Jonnalagadda, Uppugunduru Anil Kumar, Rishi Thotli, Satvik Sardesai, Sreehari Veeramachaneni, Syed Ershad Ahmed

“…This becomes especially useful for performing error-tolerant tasks like deep learning inference computation where low latency and area are a priority. …”
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Signal Recognition for English Speech Translation Based on Improved Wavelet Denoising Method by Zhuo Chen

“…Based on this, this paper will improve the traditional wavelet denoising algorithm, abandon the single-threshold judgment of the original traditional algorithm, innovatively adopt the combination of soft threshold and hard threshold, further solve the distortion problem of the denoising algorithm in the process of English speech translation signal recognition, improve the signal-to-noise ratio of English speech recognition, and further reduce the root mean square error of the signal. Good noise reduction effect is realized, and the accuracy of speech recognition is improved. …”
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A Polar Coding Scheme With Selected Index Modulation by Si-Yu Zhang, Jia-Qi Zhang, Xin-Wei Yue, Chao-Wei Wang

“…Simulation results indicate that in Orthogonal Frequency Division Multiplexing (OFDM) systems, compared to conventional polar codes and existing IM-aided polar coding schemes, the proposed PC-SIM scheme significantly improves error performance, coding rate, and PAPR reduction. …”
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A Study of Multi-distributed Resource Equalization Allocation for Virtual Power Plants Based on Genetic-heuristic Algorithm by Haifeng Li, Tao Jin, Xian Xu, Lin Shi

“…The algorithm demonstrates fast convergence, yielding solutions in less than 0.6 s across 14 repeated experiments, with an average convergence time reduction of 42% compared to traditional algorithms. …”
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Combination of machine learning and Raman spectroscopy for prediction of drug release in targeted drug delivery formulations by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…The key innovation lies in integrating these non-linear regression models with robust data preprocessing steps, including dimensionality reduction via Principal Component Analysis (PCA), categorical feature encoding through Leave-One-Out (LOO), and outlier detection using Isolation Forest. …”
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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…The experimental outcomes highlight significant advancements in convergence rates and error reduction, particularly in complex models like 3-layer-wrapped Bidirectional Long Short-Term Memory (3wBiLSTM). …”
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Design of an Improved Model for Anomaly Detection in CCTV Systems Using Multimodal Fusion and Attention-Based Networks by V. Srilakshmi, Sai Babu Veesam, Mallu Shiva Rama Krishna, Ravi Kumar Munaganuri, Dulam Devee Sivaprasad

“…In particular, accuracy improved by 5% using MDBM, the false positive rate reduced by 15% with MVAE, a more than 10% improvement in the F1-score with the attentive fusion network, a 20% reduction in reconstruction error with Deep Convolutional Autoencoder (DCA), detection precision improved by 12% using Adversarially Learned Inference (ALI) and a gain of 8% in Area Under the Curve (AUC) using Deep InfoMax (DIM) operations.…”
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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…Specifically, it has been demonstrated to achieve a 22.6% reduction in root-mean-square error (RMSE) and a 16.7% decrease in training time when compared to traditional models. …”
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Adaptive delta modulation method for arbitrary adaptation coefficients in the sensor network of the mobile ECG monitoring by О. В. Тимченко, В. І. Лозинський

“…However, the optimality of its value for reducing the quantization error of the adaptive delta encoder was not considered. …”
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Modified SLAM for Agricultural Robot Navigation by N. V. Gapon, V. V. Voronin, D. V. Rudoy, M. M. Zhdanova

“…The results show a reduction in Absolute Trajectory Error from 0.62 meters to 0.25 meters, and a decrease in Root Mean Square Error from 0.85 meters to 0.39 meters. …”
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