3 citations · 5 across the 5 of their papers we have counts for
6 papers
A DNN based Normalized Time-frequency Weighted Criterion for Robust Wideband DoA Estimation
Kuan-Lin Chen, Ching-Hua Lee, Bhaskar D. Rao +1
Deep neural networks (DNNs) have greatly benefited direction of arrival (DoA) estimation methods for speech source localization in noisy environments. However, their localization a…
Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions
Kuan-Lin Chen, Harinath Garudadri, Bhaskar D. Rao
A deep neural network using rectified linear units represents a continuous piecewise linear (CPWL) function and vice versa. Recent results in the literature estimated that the numb…
A Generalized Proportionate-Type Normalized Subband Adaptive Filter
Kuan-Lin Chen, Ching-Hua Lee, Bhaskar D. Rao +1
We show that a new design criterion, i.e., the least squares on subband errors regularized by a weighted norm, can be used to generalize the proportionate-type normalized subband a…
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
Kuan-Lin Chen, Ching-Hua Lee, Harinath Garudadri +1
Models recently used in the literature proving residual networks (ResNets) are better than linear predictors are actually different from standard ResNets that have been widely used…
Speech Recovery for Real-World Self-powered Intermittent Devices
Yu-Chen Lin, Tsun-An Hsieh, Kuo-Hsuan Hung +4
The incompleteness of speech inputs severely degrades the performance of all the related speech signal processing applications. Although many researches have been proposed to addre…
A Unified Framework for Sparse Non-Negative Least Squares using Multiplicative Updates and the Non-Negative Matrix Factorization Problem
Igor Fedorov, Alican Nalci, Ritwik Giri +3
We study the sparse non-negative least squares (S-NNLS) problem. S-NNLS occurs naturally in a wide variety of applications where an unknown, non-negative quantity must be recovered…