Results 91 to 100 of about 36,988 (280)

Generalised MBER-based vector precoding design for multiuser transmission

, 2011
We propose a generalized vector precoding (VP) design based on the minimum bit error rate (MBER) criterion for multiuser transmission in the downlink of a multiuser system, where the base station (BS) equipped with multiple transmitting antennas ...
Chen, Sheng, Hanzo, Lajos, Yao, Wang
core  

Adaptive minimum error-rate filtering design: a review

, 2008
Adaptive filtering has been an enabling technology and has found ever-increasing applications in various state-of-the-art communication systems. Traditionally, adaptive filtering has been developed based on the Wiener or minimum mean square error (MMSE ...
Sheng Chen, Lei Xu, Chen, Sheng, Xu, Lei, Shuang Tan, Tan, Shuang, Hanzo, Lajos, Lajos Hanzo   +7 more
core   +1 more source

Learning Moisture‐Induced Damage From Vision: Diffusion Models for Real‐Time Monitoring of Additive Manufacturing Processes

Advanced Science, EarlyView.
We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung, Yuna Yoo, Dharneedar Ravichandran, Dahyun Daniel Lim, Grace X. Gu   +4 more
wiley   +1 more source

Perlukah Cross Validation dilakukan? Perbandingan antara Mean Square Prediction Error dan Mean Square Error sebagai Penaksir Harapan Kuadrat Kekeliruan Model

, 2009
Seleksi model merupakan tahapan terakhir dari suatu analisis regresi. Salah satu pendekatan yang sering dipergunkan adalah cross-validation. Ukuran mean square prediction error (MSPE) dianggap sebagai ukuran yang lebih baik untuk mengevaluasi tingkat ...
Yusep, Suparman
core  

Tracking MSE performance analysis of the ∈-NSLMS algorithm

, 2015
In this paper, the tracking behavior of the ∈-normalized sign-error least mean square (NSLMS) algorithm is analyzed in the presence of white and correlated Gaussian regressors.
Zerguine, A., Ulla Faiz, M., Asad, S.M., Faiz, M.M.U., Mahmood, K.   +4 more
core   +1 more source

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

Nonasymptotic bounds on the mean square error for MCMC estimates via renewal techniques [PDF]

, 2011
The Nummellin’s split chain construction allows to decompose a Markov chain Monte Carlo (MCMC) trajectory into i.i.d. "excursions". Regenerative MCMC algorithms based on this technique use a random number of samples.
Miasojedow, Błażej, Łatuszyński, Krzysztof, Niemiro, Wojciech   +2 more
core  

Determination the smoothing constant that minimizes mean absolute error and mean square deviation

, 2021
Exponential smoothing technique has become one of the quantitative techniques are very important in forecasting. The accuracy of forecasting based on this method depends on a parameter called the smoothing constant.
Mukarromah, Z., Susilo, I.G., Pratama, D.A., Bon, A.T., Prabowo, A., Mamat, M., Sukono, ., Tripena, A.   +7 more
core  

Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer

Advanced Science, EarlyView.
This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu, Xia Ling, Xianhe Zhang, Chuanjiang Jian, Leilei Shi, Wentao Song, Xiaonan Wang, Bin Liu   +7 more
wiley   +1 more source

Comparison of AI Models for Predicting Shelf Life of Roasted Coffee Drink

Transactions on Informatics and Data Science
This paper explores the application of artificial intelligence (AI), specifically artificial neural networks (ANN), to predict the shelf life of roasted coffee beverages. The research focuses on two advanced AI models: a competitive neural network based
Sumit Goyal
doaj   +1 more source