Robust equalization of multichannel acoustic systems

In most real-world acoustical scenarios, speech signals captured by distant microphones from a source are reverberated due to multipath propagation, and the reverberation may impair speech intelligibility. Speech dereverberation can be achieved by equalizing the channels from the source to microphones. Equalization systems can be computed using estimates of multichannel acoustic impulse responses. However, the estimates obtained from system identification always include errors; the fact that an equalization system is able to equalize the estimated multichannel acoustic system does not mean that it is able to equalize the true system. The objective of this thesis is to propose and investigate robust equalization methods for multichannel acoustic systems in the presence of system identification errors. Equalization systems can be computed using the multiple-input/output inverse theorem or multichannel least-squares method. However, equalization systems obtained from these methods are very sensitive to system identification errors. A study of the multichannel least-squares method with respect to two classes of characteristic channel zeros is conducted. Accordingly, a relaxed multichannel least- squares method is proposed. Channel shortening in connection with the multiple- input/output inverse theorem and the relaxed multichannel least-squares method is discussed. Two algorithms taking into account the system identification errors are developed. Firstly, an optimally-stopped weighted conjugate gradient algorithm is proposed. A conjugate gradient iterative method is employed to compute the equalization system. The iteration process is stopped optimally with respect to system identification errors. Secondly, a system-identification-error-robust equalization method exploring the use of error models is presented, which incorporates system identification error models in the weighted multichannel least-squares formulation

Adaptive Digital Twin for UAV-Assisted Integrated Sensing, Communication, and Computation Networks

In this paper, we study a digital twin (DT)-empowered integrated sensing, communication, and computation network. Specifically, the users perform radar sensing and computation offloading on the same spectrum, while unmanned aerial vehicles (UAVs) are deployed to provide edge computing service. We first formulate a multi-objective optimization problem to minimize the beampattern performance of multi-input multi-output (MIMO) radars and the computation offloading energy consumption simultaneously. Then, we explore the prediction capability of DT to provide intelligent offloading decision, where the DT estimation deviation is considered. To track this challenge, we reformulate the original problem as a multi-agent Markov decision process and design a multi-agent proximal policy optimization (MAPPO) framework to achieve a flexible learning policy. Furthermore, the Beta-policy and attention mechanism are used to improve the training performance. Numerical results show that the proposed method is able to balance the performance tradeoff between sensing and computation functions, while reducing the energy consumption compared with the existing studies.Comment: 14 pages, 11 figures

Hydrothermal Formation of the Head-to-Head Coalesced Szaibelyite MgBO2(OH) Nanowires

The significant effect of the feeding mode on the morphology and size distribution of the hydrothermal synthesized MgBO2(OH) is investigated, which indicates that, slow dropping rate (0.5 drop s−1) and small droplet size (0.02 mL d−1) of the dropwise added NaOH solution are favorable for promoting the one-dimensional (1D) preferential growth and thus enlarging the aspect ratio of the 1D MgBO2(OH) nanostructures. The joint effect of the low concentration of the reactants and feeding mode on the hydrothermal product results in the head-to-head coalesced MgBO2(OH) nanowires with a length of 0.5–9.0 μm, a diameter of 20–70 nm, and an aspect ratio of 20–300 in absence of any capping reagents/surfactants or seeds

Adaptive inverse filtering of room acoustics

Equalization techniques for high order, multichannel, FIR systems are important for dereverberation of speech observed in reverberation using multiple microphones. In this case the multichannel system represents the room impulse responses (RIRs). The existence of near-common zeros in multichannel RIRs can slow down the convergence rate of adaptive inverse filtering algorithms. In this paper, the effect of common and near-common zeros on both the closed-form and the adaptive inverse filtering algorithms is studied. An adaptive shortening algorithm of room acoustics is presented based on this study. 1

Measurement-Based Delay and Doppler Characterizations for High-Speed Railway Hilly Scenario

This paper presents results for delay and Doppler spread characterization in high-speed railway (HSR) hilly scenario. To investigate the propagation characteristics in this specific terrain, a measurement campaign is conducted along the “Guangzhou-Shenzhen” HSR in China. A wideband channel sounder with 40 MHz bandwidth is used to collect raw data at 2.4 GHz band. The delay spread and Doppler frequency features are analyzed based on measured data. It is found that there are abundant multipath components (MPCs) in this scenario. We present the relationship between the delay spreads and the transceiver distances. The measured route can be divided into four areas with different delay and Doppler characteristics. Finally, a tapped delay line (TDL) model is proposed to parameterize the channel responses in the HSR hilly environment, which is supposed to provide criterions for evaluations of the radio interface and development of wireless communication system

Non-Stationarity Characterization and Geometry-Cluster-Based Stochastic Model for High-Speed Train Radio Channels

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linkIn time-variant high-speed train (HST) radio channels, the scattering environment changes rapidly with the movement of terminals, leading to a serious deterioration in communication quality. In the system- and link-level simulation of HST channels, this non-stationarity should be characterized and modeled properly. In this paper, the sizes of the quasi-stationary regions are quantified to measure the significant changes in channel statistics, namely, the average power delay profile (APDP) and correlation matrix distance (CMD), based on a measurement campaign conducted at 2.4 GHz. Furthermore, parameters of the multi-path components (MPCs) are estimated and a novel clustering-tracking-identifying algorithm is designed to separate MPCs into line-of-sight (LOS), periodic reflecting clusters (PRCs) from power supply pillars along the railway, and random scattering clusters (RSCs). Then, a non-stationary geometry-cluster-based stochastic model is proposed for viaduct and hilly terrain scenarios. Furthermore, the proposed model is verified by measured channel statistics such as the Rician K factor and the root mean square delay spread. The temporal autocorrelation function and the spatial cross-correlation function are presented. Quasi-stationary regions of the model are analyzed and compared with the measured data, the standardized IMT-Advanced (IMT-A) channel model, and a published nonstationary IMT-A channel model. The good agreement between the proposed model and the measured data demonstrates the ability of the model to characterize the non-stationary features of propagation environments in HST scenarios

A 1,000 Frames/s Programmable Vision Chip with Variable Resolution and Row-Pixel-Mixed Parallel Image Processors

A programmable vision chip with variable resolution and row-pixel-mixed parallel image processors is presented. The chip consists of a CMOS sensor array, with row-parallel 6-bit Algorithmic ADCs, row-parallel gray-scale image processors, pixel-parallel SIMD Processing Element (PE) array, and instruction controller. The resolution of the image in the chip is variable: high resolution for a focused area and low resolution for general view. It implements gray-scale and binary mathematical morphology algorithms in series to carry out low-level and mid-level image processing and sends out features of the image for various applications. It can perform image processing at over 1,000 frames/s (fps). A prototype chip with 64 × 64 pixels resolution and 6-bit gray-scale image is fabricated in 0.18 μm Standard CMOS process. The area size of chip is 1.5 mm × 3.5 mm. Each pixel size is 9.5 μm × 9.5 μm and each processing element size is 23 μm × 29 μm. The experiment results demonstrate that the chip can perform low-level and mid-level image processing and it can be applied in the real-time vision applications, such as high speed target tracking

Integrated transcriptomics, proteomics and metabolomics-based analysis uncover TAM2-associated glycolysis and pyruvate metabolic remodeling in pancreatic cancer

IntroductionTumor-associated macrophage 2 (TAM2) abundantly infiltrates pancreatic ductal adenocarcinoma (PAAD), and its interaction with malignant cells is involved in the regulation of tumor metabolism. In this study, we explored the metabolic heterogeneity involved in TAM2 by constructing TAM2-associated metabolic subtypes in PAAD.Materials and methodsPAAD samples were classified into molecular subtypes with different metabolic characteristics based on a multi-omics analysis strategy. 20 PAAD tissues and 10 normal pancreatic tissues were collected for proteomic and metabolomic analyses. RNA sequencing data from the TCGA-PAAD cohort were used for transcriptomic analyses. Immunohistochemistry was used to assess TAM2 infiltration in PAAD tissues.ResultsThe results of transcriptomics and immunohistochemistry showed that TAM2 infiltration levels were upregulated in PAAD and were associated with poor patient prognosis. The results of proteomics and metabolomics indicated that multiple metabolic processes were aberrantly regulated in PAAD and that this dysregulation was linked to the level of TAM2 infiltration. WGCNA confirmed pyruvate and glycolysis/gluconeogenesis as co-expressed metabolic pathways of TAM2 in PAAD. Based on transcriptomic data, we classified the PAAD samples into four TAM2-associated metabolic subtypes (quiescent, pyruvate, glycolysis/gluconeogenesis and mixed). Metabolic subtypes were each characterized in terms of clinical prognosis, tumor microenvironment, immune cell infiltration, chemotherapeutic drug sensitivity, and functional mechanisms.ConclusionOur study confirmed that the metabolic remodeling of pyruvate and glycolysis/gluconeogenesis in PAAD was closely related to TAM2. Molecular subtypes based on TAM2-associated metabolic pathways provided new insights into prognosis prediction and therapy for PAAD patients