Low-density parity check codes for partial response channels

The goals of this article are twofold: (1) to provide a brief tutorial of the application of low-density parity check (LDPC) codes for partial response (PR) channels under the framework of turbo equalization and (2) to highlight the use of structured LDPC codes in PR systems. We begin by introducing LDPC codes, their graph representations and associated sum-product decoding algorithm, followed by describing the general framework of iterative equalization and decoding approach to combat ISI. We then present explicit constructions of structured LDPC codes, which facilitate efficient implementation of encoding and decoding and show simulation results.     

Hybrid Paper–Plastic Microchip for Flexible and High‐Performance Point‐of‐Care Diagnostics

A low‐cost and easy‐to‐fabricate microchip remains a key challenge for the development of true point‐of‐care (POC) diagnostics. Cellulose paper and plastic are thin, light, flexible, and abundant raw materials, which make them excellent substrates for mass production of POC devices. Herein, a hybrid paper–plastic microchip (PPMC) is developed, which can be used for both single and multiplexed detection of different targets, providing flexibility in the design and fabrication of the microchip. The developed PPMC with printed electronics is evaluated for sensitive and reliable detection of a broad range of targets, such as liver and colon cancer protein biomarkers, intact Zika virus, and human papillomavirus nucleic acid amplicons. The presented approach allows a highly specific detection of the tested targets with detection limits as low as 10² ng mL^?1 for protein biomarkers, 10³ particle per milliliter for virus particles, and 10² copies per microliter for a target nucleic acid. This approach can potentially be considered for the development of inexpensive and stable POC microchip diagnostics and is suitable for the detection of a wide range of microbial infections and cancer biomarkers.     

Nth order current mode universal filter using MOCCCIIs

This article presents a new current mode single-input-multiple-output nth order universal filter. The proposed circuit employs (n + 1) number multiple output second generation current conveyors and n number grounded capacitors only. Presented circuits can realize current mode low pass, high pass, band pass, notch and all pass responses simultaneously at different high output impedance terminals. The current mode filter circuit provides low input impedance by selecting the proper value of bias current and also has high output impedance, which is suitable for cascading. The circuit offers some important features such as resistor less realization, no passive component matching constraints, low sensitivity, electronic tunability and active-C realization. The functionality of the proposed filter circuit is tested with the PSPICE simulation, which is found to agree well with the proposed theory.     

A Distortion-Sensitive Seam Carving Algorithm for Content-Aware Image Resizing

As displays become less expensive and are incorporated into more and more devices, there has been an increased focus on image resizing techniques to fill an image to an arbitrary screen size. Traditional methods such as cropping or resampling can introduce undesirable losses in information or distortion in perception. Recently, content-aware image retargeting methods have been proposed (Avidan and Shamir, ACM Trans Graphics 26(3), 2007; Guo et al., IEEE Trans Multimedia 11(5):856–867, 2009; Shamir and Avidan, Commun ACM 52(1), 2009; Simakov et al. 2008; Wolf et al. 2007), which produce exceptional results. In particular, seam carving, proposed by Avidan and Shamir, has gained attention as an effective solution. However, there are many cases where it can fail. In this paper we propose a distortion-sensitive seam carving algorithm for content-aware image resizing that improves edge preservation and decreases aliasing artifacts. In the proposed approach, we use local gradient information along with a thresholding technique to guide the seam selection process and provide a mechanism to halt seam carving when further processing would introduce unacceptable visual distortion in the resized image. Furthermore, anti-aliasing filter is used to reduce the aliasing artifacts caused by seam removal. Experiments have demonstrated superior performance over the current seam carving methods.     

Long-term thermal stability of Ti/Al/Mo/Au ohmic contacts on n-GaN

Improved performance of the ohmic contacts on n-GaN has been demonstrated with the use of MoAu as the capping layer on TiAl metallization. Contact resistance as low as 0.13 Θ-mm was achieved in these ohmic contacts when annealed at 850°C for 30 sec. We have studied the long-term thermal stability of these contacts at 500°C, 600°C, 750°C, and 850°C, respectively. The Ti/Al/Mo/Au metallization forms low contact-resistance ohmic contacts on n-GaN that are stable at 500°C and 600°C after 25 h of thermal treatment. The ohmic-contact performance degrades after 10 h of thermal treatment at 750°C, while the contacts exhibit nonlinear current-voltage (I-V) characteristics after 1 h of thermal treatment at 850°C with the formation of oxide on the surface of the contacts accompanied by surface discoloration. The intermetallic reactions taking place in the contacts during the long-term thermal treatments were studied using Auger electron spectroscopy (AES), and the surface morphology was characterized using atomic force microscopy (AFM).     

A graph-theoretic approach for studying the convergence of fractalencoding algorithm

We present a graph-theoretic interpretation of convergence of fractal encoding based on partial iterated function system (PIFS). First we have considered a special circumstance, where no spatial contraction has been allowed in the encoding process. The concept leads to the development of a linear time fast decoding algorithm from the compressed image. This concept is extended for the general scheme of fractal compression allowing spatial contraction (on averaging) from larger domains to smaller ranges. A linear time fast decoding algorithm is also proposed in this situation, which produces a decoded image very close to the result obtained by an ordinary iterative decompression algorithm.     

Supervised learning and frequency domain averaging-based adaptive channel estimation scheme for filterbank multicarrier with offset quadrature amplitude modulation

Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.     

Gain Adapted Optimum Mixture Estimation Scheme for Single Channel Speech Separation

This paper presents the proof of an Optimum mixture estimator for the single channel speech separation problem, which is a technique for separating two speech signals from a single recording of their mixture. The presented work is an attempt to solve a fundamental limitation in the current single channel speech separation techniques, in which it is assumed that the data used in the training as well as test phases of the separation model have the same energy levels. To overcome this limitation, a gain adapted Optimum mixture estimator is derived, which estimates the mixture of speech signals under the different signal-to-signal ratios (SSRs). Specifically, the speakers’ gains are incorporated as unknown parameters into the separation model, and then the estimator is derived in terms of the source distributions and SSR. It is demonstrated that the use of the Optimum mixture estimator results in the lower estimation error than the non-linear mapping (log and inverse-log operations)-based Mixture-Maximization (MixMax) or Quadratic estimators. The experimental results based on the real speech data also depict that the proposed estimator improves the mixture estimation performance significantly when compared with MixMax or Quadratic estimators with the gain adaptation.     

Emulating DC constant power load: a robust sliding mode control approach

This article presents emulation of a programmable power electronic, constant power load (CPL) using a dc/dc step-up (boost) converter. The converter is controlled by a robust sliding mode controller (SMC). A novel switching surface is proposed to ensure a required power sunk by the converter. The proposed dc CPL is simple in design, has fast dynamic response and high accuracy, and offers an inexpensive alternative to study converters for cascaded dc distribution power system applications. Furthermore, the proposed CPL is sufficiently robust against the input voltage variations. A laboratory prototype of the proposed dc CPL has been developed and validated with SMC realised through OPAL-RT platform. The capability of the proposed dc CPL is confirmed via experimentations in varied scenarios.