Jaewook Kang

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—This paper proposes a low-computational Bayesian algorithm for noisy sparse recovery (NSR), called BHT-BP. In this framework, we consider an LDPC-like measurement matrices which has a tree-structured property, and additive white Gaussian noise. BHT-BP has a joint detection-and-estimation structure consisting of a sparse support detector and a nonzero(More)
—In this paper, we introduce a new support recovery algorithm from noisy measurements called Bayesian hypothesis test via belief propagation (BHT-BP). BHT-BP focuses on sparse support recovery rather than sparse signal estimation. The key idea behind BHT-BP is to detect the support set of a sparse vector using hypothesis test where the posterior densities(More)
In this paper, we investigate a Bayesian sparse reconstruction algorithm called compressive sensing via Bayesian support detection (CS-BSD). This algorithm is quite robust against measurement noise and achieves the performance of an minimum mean square error (MMSE) estimator that has support knowledge beyond a certain SNR thredhold. The key idea behind(More)
Transparent electrodes have been widely used in electronic devices such as solar cells, displays, and touch screens. Highly flexible transparent electrodes are especially desired for the development of next generation flexible electronic devices. Although indium tin oxide (ITO) is the most commonly used material for the fabrication of transparent(More)
—In this paper, we propose a sparse recovery algorithm called detection-directed (DD) sparse estimation using Bayesian hypothesis test (BHT) and belief propagation (BP). In this framework, we consider the use of sparse-binary sensing matrices which has the tree-like property and the sampled-message approach for the implementation of BP. The key idea behind(More)
Silver nanowires (AgNWs) have been successfully demonstrated to function as next-generation transparent conductive electrodes (TCEs) in organic semiconductor devices owing to their figures of merit, including high optical transmittance, low sheet resistance, flexibility, and low-cost processing. In this article, high-quality, solution-processed AgNWs with(More)
—One of the challenges in Big Data is efficient handling of high-dimensional data or signals. This paper proposes a novel AMP algorithm for solving high-dimensional linear systems Y = HX + W ∈ R M which has a piecewise-constant solution X ∈ R N , under a compressed sensing framework (M ≤ N). We refer to the proposed AMP as ssAMP. This ssAMP algorithm is(More)
A novel approach for the fabrication of ultra-smooth and highly bendable substrates consisting of metal grid-conducting polymers that are fully embedded into transparent substrates (ME-TCEs) was successfully demonstrated. The fully printed ME-TCEs exhibited ultra-smooth surfaces (surface roughness ~1.0 nm), were highly transparent (~90% transmittance at a(More)
—Approximate message-passing (AMP) method is a simple and efficient framework for the linear inverse problems. In this letter, we propose a faster AMP to solve the L1-Split-Analysis for the 2D sparsity separation, which is referred to as MixAMP. We develop the MixAMP based on the factor graphical modeling and the min-sum message-passing. Then, we examine(More)