Speech Denoising via Low‐Rank and Sparse Matrix Decomposition

In this letter, we propose an unsupervised framework for speech noise reduction based on the recent development of low‐rank and sparse matrix decomposition. The proposed framework directly separates the speech signal from noisy speech by decomposing the noisy speech spectrogram into three submatrices: the noise structure matrix, the clean speech structure matrix, and the residual noise matrix. Evaluations on the Noisex‐92 dataset show that the proposed method achieves a signal‐to‐distortion ratio approximately 2.48 dB and 3.23 dB higher than that of the robust principal component analysis method and the non‐negative matrix factorization method, respectively, when the input SNR is ?5 dB.     

A Low‐Complexity Planar Antenna Array for Wireless Communication Applications: Robust Source Localization in Impulsive Noise

This paper proposes robust source localization methods for estimating the azimuth angle, elevation angle, velocity, and range using a low‐complexity planar antenna array in impulsive non‐Gaussian noise environments. The proposed robust source localization methods for wireless communication applications are based on nonlinear M‐estimation provided from Huber and Hampel. Simulation results show the robustness performance of the proposed robust methods in impulsive non‐Gaussian noise.     

Sparse least mean fourth algorithm for adaptive channel estimation in low signal‐to‐noise ratio region

Both least mean square (LMS) and least mean fourth (LMF) are popular adaptive algorithms with application to adaptive channel estimation. Because the wireless channel vector is often sparse, sparse LMS‐based approaches have been proposed with different sparse penalties, for example, zero‐attracting LMS and L_p‐norm LMS. However, these proposed methods lead to suboptimal solutions in low signal‐to‐noise ratio (SNR) region, and the suboptimal solutions are caused by LMS‐based algorithms that are sensitive to the scaling of input signal and strong noise. Comparatively, LMF can achieve better solution in low SNR region. However, LMF cannot exploit the sparse information because the algorithm depends only on its adaptive updating error but neglects the inherent sparse channel structure. In this paper, we propose several sparse LMF algorithms with different sparse penalties to achieve better solution in low SNR region and take the advantage of channel sparsity at the same time. The contribution of this paper is briefly summarized as follows: (1) construct the cost functions of the LMF algorithm with different sparse penalties; (2) derive their lower bounds; and (3) provide experiment results to show the performance advantage of the propose method in low SNR region. Copyright © 2013 John Wiley & Sons, Ltd.     

Functional and Well‐Defined β‐Sheet‐Assembled Porous Spherical Shells by Surface‐Guided Peptide Formation

Polypeptides have attracted widespread attention as building blocks for complex materials due to their ability to form higher‐ordered structures such as β‐sheets. However, the ability to precisely control the formation of well‐defined β‐sheet‐assembled materials remains challenging as β‐sheet formation tends to lead to ill‐defined and unprocessable aggregates. This work reports a simple, rapid, and robust strategy to form well‐defined peptide β‐sheet‐assembled shells (i.e., hollow spheres) by employing surface‐initiated N‐carboxyanhydride ring‐opening polymerization under a highly efficient surface‐driven approach. The concept is demonstrated by the preparation of enzyme‐degradable rigid shell architectures composed of H‐bonded poly(L‐valine) (PVal) grafts with porous and sponge‐like surface morphology. The porous PVal‐shells exhibit a remarkable and unprecedented ability to non‐covalently entrap metal nanoparticles, proteins, drug molecules, and biorelevant polymers, which could potentially lead to a diverse range of biodegradable and functional platforms for applications ranging from therapeutic delivery to organic catalysis.     

Music/Voice Separation Based on Kernel Back‐Fitting Using Weighted β‐Order MMSE Estimation

Recent developments in the field of separation of mixed signals into music/voice components have attracted the attention of many researchers. Recently, iterative kernel back‐fitting, also known as kernel additive modeling, was proposed to achieve good results for music/voice separation. To obtain minimum mean square error (MMSE) estimates of short‐time Fourier transforms of sources, generalized spatial Wiener filtering (GW) is typically used. In this paper, we propose an advanced music/voice separation method that utilizes a generalized weighted β‐order MMSE estimation (WbE) based on iterative kernel back‐fitting (KBF). In the proposed method, WbE is used for the step of mixed music signal separation, while KBF permits kernel spectrogram model fitting at each iteration. Experimental results show that the proposed method achieves better separation performance than GW and existing Bayesian estimators.     

Efficient Assembly of Bridged β‐Ga2O3 Nanowires for Solar‐Blind Photodetection

An increasing number of applications using ultraviolet radiation have renewed interest in ultraviolet photodetector research. Particularly, solar‐blind photodetectors sensitive to only deep UV (<280 nm), have attracted growing attention because of their wide applicability. Among recent advances in UV detection, nanowire (NW)‐based photodetectors seem promising, however, none of the reported devices possesses the required attributes for practical solar‐blind photodetection, namely, an efficient fabrication process, a high solar light rejection ratio, a low photocurrent noise, and a fast response. Herein, the assembly of β‐Ga₂O₃ NWs into high‐performance solar‐blind photodetectors by use of an efficient bridging method is reported. The device is made in a single‐step chemical vapor deposition process and has a high 250‐to‐280‐nm rejection ratio (～2 × 10³), low photocurrent fluctuation (<3%), and a fast decay time (<<20 ms). Further, variations in the synthesis parameters of the NWs induce drastic changes in the photoresponse properties, which suggest a possibility for tuning the performance of the photodetectors. The efficient fabrication method and high performance of the bridged β‐Ga₂O₃ NW photodetectors make them highly suitable for solar‐blind photodetection.     

一种新的融合小波变换与低秩矩阵恢复的图像去噪算法

针对小波阈值图像去噪会引入量化噪声和阈值选取不当会损失图像本身有用信息的问题,提出一种新的融合小波变换与低秩矩阵恢复(Low Rank Matrtix Recovery,LRMR)的图像去噪算法.不同于传统的单一阈值的去噪算法,所提出的算法在单一阈值上结合了低秩矩阵恢复算法,这样不仅能进一步消除噪声,同时还能修复被噪声损坏的数据,而且更能适应各种不同的噪声环境.首先,选取固定阈值对图像矩阵进行小波去噪处理.其次,采用增广拉格朗日乘子算法最小化矩阵核范数.最后,将矩阵分解为低秩逼近矩阵和稀疏误差矩阵.实验结果表明,算法获得了较高的峰值信噪比,在不同噪声环境下有较高的鲁棒性.     

Two‐Microphone Generalized Sidelobe Canceller with Post‐Filter Based Speech Enhancement in Composite Noise

This paper describes an algorithm to suppress composite noise in a two‐microphone speech enhancement system for robust hands‐free speech communication. The proposed algorithm has four stages. The first stage estimates the power spectral density of the residual stationary noise, which is based on the detection of nonstationary signal‐dominant time‐frequency bins (TFBs) at the generalized sidelobe canceller output. Second, speech‐dominant TFBs are identified among the previously detected nonstationary signal‐dominant TFBs, and power spectral densities of speech and residual nonstationary noise are estimated. In the final stage, the bin‐wise output signal‐to‐noise ratio is obtained with these power estimates and a Wiener post‐filter is constructed to attenuate the residual noise. Compared to the conventional beamforming and post‐filter algorithms, the proposed speech enhancement algorithm shows significant performance improvement in terms of perceptual evaluation of speech quality.     

A bias‐compensated proportionate NLMS algorithm with noisy input signals

This paper proposes a novel proportionate normalized least‐mean‐squares (PNLMS) algorithm that is robust to input noises. Through compensating for biases due to input noise added at the filter input, the proposed PNLMS algorithm avoids performance deterioration owing to the noisy input signals. Moreover, since the proposed PNLMS algorithm uses a new gain‐distribution matrix, it has a fast convergence rate compared with the existing PNLMS algorithms, even when there is no input noise. The experimental results verify that the proposed PNLMS algorithm enhances the filter performance for sparse system identification in the presence of input noises.     

Carbonyl‐β‐Cyclodextrin as a Novel Binder for Sulfur Composite Cathodes in Rechargeable Lithium Batteries

As one of the essential components in electrodes, the binder affects the performance of a rechargeable battery. By modifying β‐cyclodextrin (β‐CD), an appropriate binder for sulfur composite cathodes is identified. Through a partial oxidation reaction in H₂O₂ solution, β‐CD is successfully modified to carbonyl‐β‐cyclodextrin (C‐β‐CD), which exhibits a water solubility ca. 100 times that of β‐CD at room temperature. C‐β‐CD possesses the typical properties of an aqueous binder: strong bonding strength, high solubility in water, moderate viscosity, and wide electrochemical windows. Sulfur composite cathodes with C‐β‐CD as the binder demonstrate a high reversible capacity of 694.2 mA h g_(composite)^?1 and 1542.7 mA h g_(sulfur)^?1, with a sulfur utilization approaching 92.2%. The discharge capacity remains at 1456 mA h g_(sulfur)^?1 after 50 cycles, which is much higher than that of the cathode with unmodified β‐CD as binder. Combined with its low cost and environmental benignity, C‐β‐CD is a promising binder for sulfur cathodes in rechargeable lithium batteries with high electrochemical performance.     

Non‐binary protograph low‐density parity‐check codes for space communications

Protograph‐based non‐binary low‐density parity‐check (LDPC) codes with ultra‐sparse parity‐check matrices are compared with binary LDPC and turbo codes (TCs) from space communication standards. It is shown that larger coding gains are achieved, outperforming the binary competitors by more than 0.3 dB on the additive white Gaussian noise channel (AWGN). In the short block length regime, the designed codes gain more than 1 dB with respect to the binary protograph LDPC codes recently proposed for the next generation up‐link standard of the Consultative Committee for Space Data Systems. Copyright © 2012 John Wiley & Sons, Ltd.     

A New Prototype Two‐Phase (TiNi)–(β‐W) SMA System with Tailorable Thermal Hysteresis

The Ti–Ni–W two‐phase shape memory alloy (SMA) thin film system is presented as a prototype for new SMAs with tailorable thermal transformation hysteresis (ΔT). The concept is to combine the SMA TiNi with almost insoluble W to create the two‐phase system (TiNi)–(β‐W). This system behaves like a pseudobinary TiNi system. Phase transformation behavior for compositions above the solubility limit of W in TiNi exhibit a B2–R phase transformation with characteristically small ΔT. Moreover, ΔT is dependent on the amount of W and it can be tailored to zero and even negative. This phenomenon is rationalized as being due to the mechanical interaction between the phases B2‐TiNi and β‐W. The presented results are very promising for the development of high‐speed Ti–Ni‐based SMA actuators.     

A novel compressed sensing ultra‐wideband channel estimation method based on non‐convex optimization

Due to the low power spectral density and complicated transfer propagation of ultra‐wideband (UWB) signal, it is important to estimate UWB channel accurately. But it is difficult to sample UWB signals directly due to their wider band width. However, compressed sensing (CS) theory provides a feasible way through lower sampling speed. Common CS‐UWB channel estimation methods adopt convex optimization, non‐sparse or non‐restricted form. In order to strengthen the restriction on sparsity of the reconstructed channel vector, a non‐convex optimization method is proposed in this paper to estimate UWB channel. Proposed method sets the objective function as a non‐convex optimization model using l_p–norm. This model is combined as a convex function to approximate the objective function and reconstruct the UWB channel vector iteratively. Because l_p–norm is closer to l₀–norm than l₁ and l₂–norm, its restriction on sparsity of objective vector is stricter. The simulation results show that this method can enhance reconstruction performance compared with existing CS‐UWB channel estimation methods. Copyright © 2013 John Wiley & Sons, Ltd.     

Robust Speech Hash Function

In this letter, we present a new speech hash function based on the non‐negative matrix factorization (NMF) of linear prediction coefficients (LPCs). First, linear prediction analysis is applied to the speech to obtain its LPCs, which represent the frequency shaping attributes of the vocal tract. Then, the NMF is performed on the LPCs to capture the speech's local feature, which is then used for hash vector generation. Experimental results demonstrate the effectiveness of the proposed hash function in terms of discrimination and robustness against various types of content preserving signal processing manipulations.     

Self‐Assembling Nanotubes Consisting of Rigid Cyclic γ‐Peptides

Self‐assembling cyclic peptide nanotubes (SPNs) have been extensively studied due to their potential applications in biology and material sciences. Cyclic γ‐peptides, which have a larger conformational space, have received less attention than the cyclic α‐ and β‐peptides. The self‐assembly of cyclic homo‐γ‐tetrapeptide based on cis‐3‐aminocyclohexanecarboxylic acid (γ‐Ach) residues, which can be easily synthesized by a one‐pot process is investigated. Fourier transform infrared (FTIR) and NMR analysis along with density functional theory (DFT) calculations indicate that the cyclic homo‐γ‐tetrapeptide, with a non‐planar conformation, can self‐assemble into nanotubes through hydrogen‐bond‐mediated parallel stacking. Atomic force microscopy (AFM) and transmission electron microscopy (TEM) experiments reveal the formation of bundles of nanotubes in CH₂Cl₂/hexane, but individual nanotubes and bundles of only two nanotubes are obtained in water. The integration of TEG (triethylene glycol) monomethyl ether chains and cyclopeptide backbones may allow the control of width of single nanotubes.     

非对称代价函数的稀疏卷积非负矩阵分解方法

提出一种基于非对称代价函数的稀疏卷积非负矩阵分解方法。该方法利用板仓-斋藤距离作为目标代价函数来衡量目标矩阵与重建矩阵的差异,使得较小的矩阵元素具有较小的重建误差,并且该代价函数具有尺度不变性的特点。为了考察其在弱语音成分重建方面的优势,将本文提出的算法应用于耳语音谱分解及重建实验。实验结果表明,与基于欧氏距离和基于Kullback-Leibler(K-L)散度的卷积非负矩阵分解算法相比,本文算法对于弱语音成分具有更好的重构效果,重建后的语音信号具有较大的可懂度。      

在线更新噪声基矩阵的非负矩阵分解语音增强方法

基于非负矩阵分解(Nonnegative matrix factorization, NMF)的语音增强算法需要和背景噪声类型匹配的噪声基矩阵(Basis matrix)，而在实际中，这是很难被保证的。本文提出了一种基于噪声基矩阵在线更新的非负矩阵分解语音增强方法，该方法首先利用一个无语音帧判决模块识别出带噪语音的无语音区域，然后利用一个固定长度的滑动窗口(Sliding window)来包含若干帧最近过去的带噪语音的无语音帧，并用这些无语音帧的幅度谱在线更新噪声基矩阵，最后利用更新得到的噪声基矩阵和预先训练的语音基矩阵实现语音增强。该方法能够在线更新出匹配的噪声基矩阵，有效地解决了噪声基矩阵不匹配的问题。实验证明，本文所提的方法在线学习到的噪声基矩阵在大多数条件下比匹配训练集下训练得到的噪声基矩阵的性能还要优越。      

Reduced‐rank space–time adaptive interference suppression for navigation systems based on QR decomposition and approximations of basis functions

This paper presents a novel reduced‐rank space–time adaptive processing (STAP) algorithm for interference suppression in global positioning system (GPS) receivers with low computational complexity for protection against the multipath and jamming interferences. The proposed STAP algorithm is based on the least‐squares (LS) criterion to jointly optimize a projection matrix, which is used for dimensionality reduction, and the reduced‐rank filter. The main novelties are the design of the projection matrix based on approximations of basis functions, the pattern matching between the projection matrix and the received data, and the derivation of a QR decomposition‐based reduced‐rank recursive LS algorithm for practical implementations. The proposed scheme works on an instantaneous basis, i.e. at each time instant, the most suitable pattern and the rank of the projection matrix are selected to reduce the dimensionality of the received data aiming at minimizing the squared error, while using an improved search algorithm to save the effort in finding the best projection matrix. Simulation results in a GPS system show that compared to existing reduced‐rank and full‐rank algorithms, the proposed algorithm has a much lower computational complexity, and remarkably better performance for interference suppression. Copyright © 2011 John Wiley & Sons, Ltd.     

Self‐Assembled Robust Dipeptide Nanotubes and Fabrication of Dipeptide‐Capped Gold Nanoparticles on the Surface of these Nanotubes

Three water‐soluble dipeptides containing N‐terminally located β‐alanine residue and C‐terminally located α‐amino acid residues (β‐Ala‐L ‐Xaa, Xaa = Val/Ile/Phe) form robust crystalline nanotubes. These dipeptide nanotubes contain a common motif, a hybrid of β,α‐amino acids, which are stable against heat up to 80 °C, a wide range of pH (2–10), and proteolytic degradation. These robust crystalline dipeptide nanotubes are used as a template for fabricating dipeptide‐capped gold nanoparticles on their outer surfaces. This is an easy way to develop nanotube/nanoparticle hybrid materials under mild conditions.