Sparse complex FxLMS for active noise cancellation over spatial regions

In this paper, we investigate active noise control over large 2D spatial regions when the noise source is sparsely distributed. The l1 relaxation technique originated from compressive sensing is adopted and based on that we develop the algorithm for two cases: multipoint noise cancellation and wave domain noise cancellation. This results in two new variants (i) zero-attracting multi-point complex FxLMS and (ii) zero-attracting wave domain complex FxLMS. Both approaches use a feedback control system, where a microphone array is distributed over the boundary of the control region to measure the residual noise signals and a loudspeaker array is placed outside the microphone array to generate the anti-noise signals. Simulation results demonstrate the performance and advantages of the proposed methods in terms of convergence rate and spatial noise reduction levels.This work is supported by Australian Research Council (ARC) Discovery Projects funding scheme (project no. DP140103412). The work of J. Zhang was sponsored by the China Scholarship Council with the Australian National University

Active Noise Control Over Space: A Wave Domain Approach

Noise control and cancellation over a spatial region is a fundamental problem in acoustic signal processing. In this paper, we utilize wave-domain adaptive algorithms to iteratively calculate the secondary source driving signals and to cancel the primary noise field over the control region. We propose wave-domain active noise control algorithms based on two minimization problems: first, minimizing the wave-domain residual signal coefficients, and second, minimizing the acoustic potential energy over the region, and derive the update equations with respect to two variables, the loudspeaker weights and wave-domain secondary source coefficients. Simulation results demonstrate the effectiveness of the proposed algorithms, more specifically the convergence speed and the noise cancellation performance in terms of the noise reduction level and acoustic potential energy reduction level over the entire spatial region.DP14010341

Multichannel active noise control for spatially sparse noise fields

Multi-channel active noise control (ANC) is currently an attractive solution for the attenuation of low-frequency noise fields, in three-dimensional space. This paper develops a controller for the case when the noise source components are sparsely distributed in space. The anti-noise signals are designed as in conventional ANC to minimize the residual errors but with an additional term containing an ℓl norm regularization applied to the signal magnitude. This results in that only secondary sources close to the noise sources are required to be active for cancellation of sparse noise fields. Adaptive algorithms with low computational complexity and faster convergence speeds are propose

Are Th17 Cells an Appropriate New Target in the Treatment of Rheumatoid Arthritis?

Th17 cells play crucial roles not only in host defense but also in many human autoimmune diseases and corresponding animal models. Although many of the fundamental principles regarding Th17 biology have been rapidly elucidated in mice, there remain numerous controversies regarding the differentiation, plasticity, and pathogenicity of human Th17 cells. In this review, we consider these open questions in comparison to what has already been clarified in mice, and discuss the potential impact of discoveries related to the Th17 pathway on the development of new therapeutic strategies in Th17 driven autoimmune diseases, specifically rheumatoid arthritis. Clin Trans Sci 2010; Volume 3: 319–326Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79296/1/j.1752-8062.2010.00233.x.pd

CD14 Signaling Restrains Chronic Inflammation through Induction of p38-MAPK/SOCS-Dependent Tolerance

Current thinking emphasizes the primacy of CD14 in facilitating recognition of microbes by certain TLRs to initiate pro-inflammatory signaling events and the importance of p38-MAPK in augmenting such responses. Herein, this paradigm is challenged by demonstrating that recognition of live Borrelia burgdorferi not only triggers an inflammatory response in the absence of CD14, but one that is, in part, a consequence of altered PI3K/AKT/p38-MAPK signaling and impaired negative regulation of TLR2. CD14 deficiency results in increased localization of PI3K to lipid rafts, hyperphosphorylation of AKT, and reduced activation of p38. Such aberrant signaling leads to decreased negative regulation by SOCS1, SOCS3, and CIS, thereby compromising the induction of tolerance in macrophages and engendering more severe and persistent inflammatory responses to B. burgdorferi. Importantly, these altered signaling events and the higher cytokine production observed can be mimicked through shRNA and pharmacological inhibition of p38 activity in CD14-expressing macrophages. Perturbation of this CD14/p38-MAPK-dependent immune regulation may underlie development of infectious chronic inflammatory syndromes

A Kernel Least Mean Square Algorithm Based on Randomized Feature Networks

To construct an online kernel adaptive filter in a non-stationary environment, we propose a randomized feature networks-based kernel least mean square (KLMS-RFN) algorithm. In contrast to the Gaussian kernel, which implicitly maps the input to an infinite dimensional space in theory, the randomized feature mapping transform inputs samples into a relatively low-dimensional feature space, where the transformed samples are approximately equivalent to those in the feature space using a shift-invariant kernel. The mean square convergence process of the proposed algorithm is investigated under the uniform convergence analysis method of a nonlinear adaptive filter. The computational complexity is also evaluated. In Lorenz time series prediction and nonstationary channel equalization scenarios, the simulation results demonstrate the effectiveness of the proposed algorithm

A Parallel Search Strategy Based on Sparse Representation for Infrared Target Tracking

A parallel search strategy based on sparse representation (PS-L1 tracker) is proposed in the particle filter framework. To obtain the weights of state particles, target templates are represented linearly with the dictionary of target candidates. Sparse constraints on the coefficient guarantee that only true target candidates can be selected, and the nonnegative entries denote the associate weights of efficient target states. Then the optimal target state can be estimated by the linear combination of above weighted states. In this way, efficient target states are selected simultaneously from all the particles, which we call a parallel search strategy. Experimental results demonstrate excellent performance of the proposed method on challenging infrared images

Extended Covering Arrays for Sequence Coverage

Although combinatorial testing has been widely studied and used, there are still some situations and requirements that combinatorial testing does not apply to well, such as a system under test whose test cases need to be performed contiguously. For thorough testing, the testing requirements are not only to cover all the interactions among factors but also to cover all the value sequences of every factor. Generally, systems under test always involve constraints and dependencies in or among test cases. The constraints among test cases have not been effectively specified. First, we introduce extended covering arrays that can achieve both t-way combinatorial coverage and t-wise sequence coverage, and propose a clocked computation tree logic-based formal specification method for specifying constraints. Then, Particle Swarm Optimization (PSO) based Extended covering array Generator (PEG) is elaborated. To evaluate the constructed test suites, a method for verifying the constraints’ validity is presented, and kernel functions for measuring the coverage are also introduced. Finally, the performance of the proposed PEG is evaluated using several sets of benchmark experiments for some common constraints, and the feasibility and usefulness of PEG is validated