A New Variable Regularized Transform Domain NLMS Adaptive Filtering Algorithm-Acoustic Applications and Performance Analysis

published_or_final_versio

Photoemission Spectroscopy of Magnetic and Non-magnetic Impurities on the Surface of the Bi2_2Se3_3 Topological Insulator

Dirac-like surface states on surfaces of topological insulators have a chiral spin structure that suppresses back-scattering and protects the coherence of these states in the presence of non-magnetic scatterers. In contrast, magnetic scatterers should open the back- scattering channel via the spin-flip processes and degrade the state's coherence. We present angle-resolved photoemission spectroscopy studies of the electronic structure and the scattering rates upon adsorption of various magnetic and non-magnetic impurities on the surface of Bi$_2$Se$_3$, a model topological insulator. We reveal a remarkable insensitivity of the topological surface state to both non-magnetic and magnetic impurities in the low impurity concentration regime. Scattering channels open up with the emergence of hexagonal warping in the high-doping regime, irrespective of the impurity's magnetic moment.Comment: 5 pages, 4 figure

Channel Estimation for RIS-Aided MIMO Systems: A Partially Decoupled Atomic Norm Minimization Approach

Channel estimation (CE) plays a key role in reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output (MIMO) communication systems, while it poses a challenging task due to the passive nature of RIS and the cascaded channel structures. In this paper, a partially decoupled atomic norm minimization (PDANM) framework is proposed for CE of RIS-aided MIMO systems, which exploits the three-dimensional angular sparsity of the channel. In particular, PDANM partially decouples the differential angles at the RIS from other angles at the base station and user equipment, reducing the computational complexity compared with existing methods. A reweighted PDANM (RPDANM) algorithm is proposed to further improve CE accuracy, which iteratively refines CE through a specifically designed reweighing strategy. Building upon RPDANM, we propose an iterative approach named RPDANM with adaptive phase control (RPDANM-APC), which adaptively adjusts the RIS phases based on previously estimated channel parameters to facilitate CE, achieving superior CE accuracy while reducing training overhead. Numerical simulations demonstrate the superiority of our proposed approaches in terms of running time, CE accuracy, and training overhead. In particular, the RPDANM-APC approach can achieve higher CE accuracy than existing methods within less than 40 percent training overhead while reducing the running time by tens of times.Comment: 35 pages, 9 figures. Part of this paper has been submitted to the 2023 IEEE Global Communications Conference (GLOBECOM

A new regularized TVAR-based algorithm for recursive detection of nonstationarity and its application to speech signals

This paper develops a new recursive nonstationarity detection method based on time-varying autoregressive (TVAR) modeling. A local likelihood estimation approach is introduced which gives more weights to observations near the current time instant but less to those distance apart. It thus allows the Wald test to be computed based on RLS-type algorithms with low computational cost. A reliable and efficient state regularized variable forgetting factor (VFF) QR decomposition (QRD)-based RLS (SR-VFF-QRRLS) algorithm is adopted for estimation for its asymptotically unbiased property and immunity to lacking of excitation. Advantages of the proposed approach over conventional approaches are 1) it provides continuous parameter estimates and the corresponding stationary intervals with low complexity, 2) it mitigates low excitation problems using state regularization, and 3) stationarity at different scales can be detected by appropriately choosing a certain window size. The effectiveness of the proposed algorithm is evaluated by testing vocal tract changes in real speech signals. © 2012 IEEE.published_or_final_versio

A New Variable Regularized QR Decomposition-Based Recursive Least M-Estimate Algorithm-Performance Analysis and Acoustic Applications

published_or_final_versio

A new recursive algorithm for time-varying autoregressive (TVAR) model estimation and its application to speech analysis

This paper proposes a new state-regularized (SR) and QR decomposition based recursive least squares (QRRLS) algorithm with variable forgetting factor (VFF) for recursive coefficient estimation of time-varying autoregressive (AR) models. It employs the estimated coefficients as prior information to minimize the exponentially weighted observation error, which leads to reduced variance and bias over traditional regularized RLS algorithm. It also increases the tracking speed by introducing a new measure of convergence status to control the FF. Simulations using synthetic and real speech signals show that the proposed method has improved tracking performance and reduced estimation error variance than conventional TVAR modeling methods during rapid changing of AR coefficients. © 2012 IEEE.published_or_final_versionThe 2012 IEEE International Symposium on Circuits and Systems (ISCAS), Seoul, Korea, 20-23 May 2012. In IEEE International Symposium on Circuits and Systems Proceedings, 2012, p. 1026-102

Measurement of an Exceptionally Weak Electron-Phonon Coupling on the Surface of the Topological Insulator Bi2_2Se3_3 Using Angle-Resolved Photoemission Spectroscopy

Gapless surface states on topological insulators are protected from elastic scattering on non-magnetic impurities which makes them promising candidates for low-power electronic applications. However, for wide-spread applications, these states should have to remain coherent at ambient temperatures. Here, we studied temperature dependence of the electronic structure and the scattering rates on the surface of a model topological insulator, Bi$_2$Se$_3$, by high resolution angle-resolved photoemission spectroscopy. We found an extremely weak broadening of the topological surface state with temperature and no anomalies in the state's dispersion, indicating exceptionally weak electron-phonon coupling. Our results demonstrate that the topological surface state is protected not only from elastic scattering on impurities, but also from scattering on low-energy phonons, suggesting that topological insulators could serve as a basis for room temperature electronic devices.Comment: published version, 5 pages, 4 figure