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This paper proposes a hierarchical adaptive sampling scheme for passivity characterization of large-scale linear lumped macromodels. Here, large-scale is intended both in terms of dynamic order and especially number of input/output ports.…

Computational Engineering, Finance, and Science · Computer Science 2020-11-06 Marco De Stefano , Stefano Grivet-Talocia , Torben Wendt , Cheng Yang , Christian Schuster

Modern deep neural networks (DNNs) have achieved state-of-the-art performances but are typically over-parameterized. The over-parameterization may result in undesirably large generalization error in the absence of other customized training…

Machine Learning · Computer Science 2023-03-03 Jiawei Du , Daquan Zhou , Jiashi Feng , Vincent Y. F. Tan , Joey Tianyi Zhou

Graph-regularized semi-supervised learning has been used effectively for classification when (i) instances are connected through a graph, and (ii) labeled data is scarce. If available, using multiple relations (or graphs) between the…

Machine Learning · Computer Science 2015-10-22 Junting Ye , Leman Akoglu

An Adaptive Nonlinear Differential Limiter (ANDL) is proposed in this paper to efficiently alleviate the impact of impulsive noise (IN) in a communication system. Unlike existing nonlinear methods, the ANDL is implemented in the analog…

Signal Processing · Electrical Eng. & Systems 2018-11-26 Reza Barazideh , Balasubramaniam Natarajan , Alexei V. Nikitin , Solmaz Niknam

This paper provides analytical performance of the low-complexity family of affine projection algorithms on the estimation of multipath Rayleigh fading channels in the presence of carrier frequency offsets (CFO) and random channel…

Numerical Analysis · Mathematics 2011-07-08 Sayed A. Hadei , Paeiz Azmi

Graph sampling addresses the problem of selecting a node subset in a graph to collect samples, so that a K-bandlimited signal can be reconstructed in high fidelity. Assuming an independent and identically distributed (i.i.d.) noise model,…

Signal Processing · Electrical Eng. & Systems 2019-10-23 Fen Wang , Gene Cheung , Yongchao Wang

In Neural Networks (NN), Adaptive Activation Functions (AAF) have parameters that control the shapes of activation functions. These parameters are trained along with other parameters in the NN. AAFs have improved performance of Neural…

Computer Vision and Pattern Recognition · Computer Science 2016-08-24 Le Hou , Dimitris Samaras , Tahsin M. Kurc , Yi Gao , Joel H. Saltz

In modern wireless networks, interference is no longer negligible since each cell becomes smaller to support high throughput. The reduced size of each cell forces to install many cells, and consequently causes to increase inter-cell…

Information Theory · Computer Science 2012-09-19 Hyukjoon Kwon , Jungwon Lee , Inyup Kang

Robust diffusion adaptive estimation algorithms based on the maximum correntropy criterion (MCC), including adaptation to combination MCC and combination to adaptation MCC, are developed to deal with the distributed estimation over network…

Machine Learning · Statistics 2016-02-04 Wentao Ma , Badong Chen , Jiandong Duan , Haiquan Zhao

Spatially selective active noise control (SSANC) hearables aim to attenuate noise from certain directions at the eardrum while preserving desired speech arriving from selected directions. Existing SSANC systems typically assume an accurate…

Audio and Speech Processing · Electrical Eng. & Systems 2026-05-19 Tong Xiao , Reinhild Roden , Matthias Blau , Simon Doclo

Multi-armed Bandit (MAB) algorithms identify the best arm among multiple arms via exploration-exploitation trade-off without prior knowledge of arm statistics. Their usefulness in wireless radio, IoT, and robotics demand deployment on edge…

Systems and Control · Electrical Eng. & Systems 2021-06-08 S. V. Sai Santosh , Sumit J. Darak

An algorithm is said to be adaptive to a certain parameter (of the problem) if it does not need a priori knowledge of such a parameter but performs competitively to those that know it. This dissertation presents our work on adaptive…

Machine Learning · Computer Science 2023-07-10 Zhenxun Zhuang

The deployment of non-binary pulse amplitude modulation (PAM) and soft decision (SD)-forward error correction (FEC) in future intensity-modulation (IM)/direct-detection (DD) links is inevitable. However, high-speed IM/DD links suffer from…

Signal Processing · Electrical Eng. & Systems 2023-09-29 Kaiquan Wu , Gabriele Liga , Jamal Riani , Alex Alvarado

In this article, we present a method for increasing adaptivity of an existing robust estimation algorithm by learning two parameters to better fit the residual distribution. The analyzed method uses these two parameters to calculate weights…

Robotics · Computer Science 2023-06-27 Shounak Das , Jason Gross

In this article, we propose an improved multiple feedback successive interference cancellation (IMF-SIC) algorithm for symbol vector detection in multiple-input multiple-output (MIMO) spatial multiplexing systems. The multiple feedback (MF)…

Information Theory · Computer Science 2015-09-03 Manish Mandloi , Mohammed Azahar Hussain , Vimal Bhatia

Diffraction limited resolution adaptive optics (AO) correction in visible wavelengths requires a high performance control. In this paper we investigate infinite impulse response filters that optimize the wavefront correction: we tested…

Instrumentation and Methods for Astrophysics · Physics 2015-06-05 G. Agapito , C. Arcidiacono , F. Quirós-Pacheco , A. Puglisi , S. Esposito

An efficient, joint transmission delay and channel parameter estimation algorithm is proposed for uplink asynchronous direct-sequence code-division multiple access (DS-CDMA) systems based on the space-alternating generalized expectation…

Information Theory · Computer Science 2016-11-17 E. Panayirci , A. Kocian , H. V. Poor , M. Ruggieri

The sum-capacity for specific sub-classes of ergodic fading Gaussian two-user interference channels (IFCs) is developed under the assumption of perfect channel state information at all transmitters and receivers. For the sub-classes of…

Information Theory · Computer Science 2016-11-17 Lalitha Sankar , Xiaohu Shang , Elza Erkip , H. Vincent Poor

We consider the problem of estimating a signal subspace in the presence of interference that contaminates some proportion of the received observations. Our emphasis is on detecting the contaminated observations so that the signal subspace…

Methodology · Statistics 2023-03-15 Robert L. Bassett , Micah Y. Oh

We propose regularized approximate message passing (RAMP), a low-complexity algorithm for discrete signal detection in overloaded multiple-input multiple-output (MIMO) systems where the number of transmit antennas exceeds the number of…

Signal Processing · Electrical Eng. & Systems 2026-04-07 Shreesal Shrestha , Getuar Rexhepi , Kuranage Roche Rayan Ranasinghe , Hyeon Seok Rou , Giuseppe Thadeu Freitas de Abreu