Two-Dimensional Noise-Predictive Maximum Likelihood Method for Magnetic Recording Channels

Noise-predictive maximum likelihood (NPML) is a well known signal detection technique used in partial response maximum likelihood (PRML) scheme in 1D magnetic recording channels. The noise samples colored by the partial response (PR) equalizer are predicted/ whitened during the signal detection using a Viterbi detector. In this paper, we propose an extension of the NPML technique for signal detection in 2D ISI channels. The impact of noise prediction during signal detection is studied in PRML scheme for a particular choice of 2D ISI channel and PR targets.

Bulk-Induced 1/f Noise at the Surface of Three-Dimensional Topological Insulators

Slow intrinsic fluctuations of resistance, also known as the flicker noise or 1/f-noise, in the surface transport of strong topological insulators (TIs) is a poorly understood phenomenon. Here, we have systematically explored the 1/f-noise in field-effect transistors (FET) of mechanically exfoliated Bi1.6Sb0.4Te2Se TI films when transport occurs predominantly via the surface states. We find that the slow kinetics of the charge disorder within the bulk of the TI induces mobility fluctuations at the surface, providing a new source of intrinsic 1/f-noise that is unique to bulk TI systems. At small channel thickness, the noise magnitude can be extremely small, corresponding to the phenomenological Hooge parameter gamma(H) as low as approximate to 10(-4), but it increases rapidly when channel thickness exceeds similar to 1 mu m. From the temperature (T)-dependence of noise, which displayed sharp peaks at characteristic values of T, we identified generation-recombination processes from interband transitions within the TI bulk as the dominant source of the mobility fluctuations in surface transport. Our experiment not only establishes an intrinsic microscopic origin of noise in TI surface channels, but also reveals a unique spectroscopic information on the impurity bands that can be useful in bulk TI systems in general.

Magnitude and Origin of Electrical Noise at Individual Grain Boundaries in Graphene

Grain boundaries (GBs) are undesired in large area layered 2D materials as they degrade the device quality and their electronic performance. Here we show that the grain boundaries in graphene which induce additional scattering of carriers in the conduction channel also act as an additional and strong source of electrical noise especially at the room temperature. From graphene field effect transistors consisting of single GB, we find that the electrical noise across the graphene GBs can be nearly 10 000 times larger than the noise from equivalent dimensions in single crystalline graphene. At high carrier densities (n), the noise magnitude across the GBs decreases as proportional to 1/n, suggesting Hooge-type mobility fluctuations, whereas at low n close to the Dirac point, the noise magnitude could be quantitatively described by the fluctuations in the number of propagating modes across the GB.

Determinantal point processes in the plane from products of random matrices

We show that the density of eigenvalues for three classes of random matrix ensembles is determinantal. First we derive the density of eigenvalues of product of k independent n x n matrices with i.i.d. complex Gaussian entries with a few of matrices being inverted. In second example we calculate the same for (compatible) product of rectangular matrices with i.i.d. Gaussian entries and in last example we calculate for product of independent truncated unitary random matrices. We derive exact expressions for limiting expected empirical spectral distributions of above mentioned ensembles.

Autoregressive cascades on random networks

A network cascade model that captures many real-life correlated node failures in large networks via load redistribution is studied. The considered model is well suited for networks where physical quantities are transmitted, e.g., studying large scale outages in electrical power grids, gridlocks in road networks, and connectivity breakdown in communication networks, etc. For this model, a phase transition is established, i.e., existence of critical thresholds above or below which a small number of node failures lead to a global cascade of network failures or not. Theoretical bounds are obtained for the phase transition on the critical capacity parameter that determines the threshold above and below which cascade appears or disappears, respectively, that are shown to closely follow numerical simulation results. (C) 2015 Elsevier B.V. All rights reserved.

Autoregressive cascades on random networks

A network cascade model that captures many real-life correlated node failures in large networks via load redistribution is studied. The considered model is well suited for networks where physical quantities are transmitted, e.g., studying large scale outages in electrical power grids, gridlocks in road networks, and connectivity breakdown in communication networks, etc. For this model, a phase transition is established, i.e., existence of critical thresholds above or below which a small number of node failures lead to a global cascade of network failures or not. Theoretical bounds are obtained for the phase transition on the critical capacity parameter that determines the threshold above and below which cascade appears or disappears, respectively, that are shown to closely follow numerical simulation results. (C) 2015 Elsevier B.V. All rights reserved.

Percolative switching in transition metal dichalcogenide field-effect transistors at room temperature

We have addressed the microscopic transport mechanism at the switching or `on-off' transition in transition metal dichalcogenide (TMDC) field-effect transistors (FETs), which has been a controversial topic in TMDC electronics, especially at room temperature. With simultaneous measurement of channel conductivity and its slow time-dependent fluctuation (or noise) in ultrathin WSe2 and MoS2 FETs on insulating SiO2 substrates where noise arises from McWhorter-type carrier number fluctuations, we establish that the switching in conventional backgated TMDC FETs is a classical percolation transition in a medium of inhomogeneous carrier density distribution. From the experimentally observed exponents in the scaling of noise magnitude with conductivity, we observe unambiguous signatures of percolation in a random resistor network, particularly, in WSe2 FETs close to switching, which crosses over to continuum percolation at a higher doping level. We demonstrate a powerful experimental probe to the microscopic nature of near-threshold electrical transport in TMDC FETs, irrespective of the material detail, device geometry, or carrier mobility, which can be extended to other classes of 2D material-based devices as well.

Tunability of 1/f Noise at Multiple Dirac Cones in hBN Encapsulated Graphene Devices

The emergence of multiple Dirac cones in hexagonal boron nitride (hBN)-graphene heterostructures is particularly attractive because it offers potentially better landscape for higher and versatile transport properties than the primary Dirac cone. However, the transport coefficients of the cloned Dirac cones is yet not fully characterized and many open questions, including the evolution of charge dynamics and impurity scattering responsible for them, have remained unexplored. Noise measurements, having the potential to address these questions, have not been performed to date in dual-gated hBN graphene hBN devices. Here, we present the low frequency 1/f noise measurements at multiple Dirac cones in hBN encapsulated single and bilayer graphene in dual-gated geometry. Our results reveal that the low-frequency noise in graphene can be tuned by more than two-orders of magnitude by changing carrier concentration as well as by modifying the band structure in bilayer graphene. We find that the noise is surprisingly suppressed at the cloned Dirac cone compared to the primary Dirac cone in single layer graphene device, while it is strongly enhanced for the bilayer graphene with band gap opening. The results are explained with the calculation of dielectric function using tight-binding model. Our results also indicate that the 1/f noise indeed follows the Hooge's empirical formula in hBN-protected devices in dual-gated geometry. We also present for the first time the noise data in bipolar regime of a graphene device.

Ellipse Fitting Using the Finite Rate of Innovation Sampling Principle

Standard approaches for ellipse fitting are based on the minimization of algebraic or geometric distance between the given data and a template ellipse. When the data are noisy and come from a partial ellipse, the state-of-the-art methods tend to produce biased ellipses. We rely on the sampling structure of the underlying signal and show that the x- and y-coordinate functions of an ellipse are finite-rate-of-innovation (FRI) signals, and that their parameters are estimable from partial data. We consider both uniform and nonuniform sampling scenarios in the presence of noise and show that the data can be modeled as a sum of random amplitude-modulated complex exponentials. A low-pass filter is used to suppress noise and approximate the data as a sum of weighted complex exponentials. The annihilating filter used in FRI approaches is applied to estimate the sampling interval in the closed form. We perform experiments on simulated and real data, and assess both objective and subjective performances in comparison with the state-of-the-art ellipse fitting methods. The proposed method produces ellipses with lesser bias. Furthermore, the mean-squared error is lesser by about 2 to 10 dB. We show the applications of ellipse fitting in iris images starting from partial edge contours, and to free-hand ellipses drawn on a touch-screen tablet.

A strategy to achieve enhanced electromagnetic interference shielding at ultra-low concentration of multiwall carbon nanotubes in P alpha MSAN/PMMA blends in the presence of a random copolymer PS-r-PMMA

A unique strategy was adopted to achieve an ultra-low electrical percolation threshold of multiwall carbon nanotubes (MWNTs) (0.25 wt%) in a classical partially miscible blend of poly-alpha-methylstyrene-co-acrylonitrile and poly(methyl methacrylate) (P alpha MSAN/PMMA), with a lower critical solution temperature. The polymer blend nanocomposite was prepared by standard melt-mixing followed by annealing above the phase separation temperature. In a two-step mixing protocol, MWNTs were initially melt-mixed with a random PS-r-PMMA copolymer and subsequently diluted with 85/15 P alpha MSAN/PMMA blends in the next mixing step. Mediated by the PS-r-PMMA, the MWNTs were mostly localized at the interface and bridged the PMMA droplets. This strategy led to enhanced electromagnetic interference (EMI) shielding effectiveness at 0.25 wt% MWNTs through multiple scattering from MWNT-covered droplets, as compared to the blends without the copolymer, which were transparent to electromagnetic radiation.

IMAGE DENOISING IN MULTIPLICATIVE NOISE

We address the problem of denoising images corrupted by multiplicative noise. The noise is assumed to follow a Gamma distribution. Compared with additive noise distortion, the effect of multiplicative noise on the visual quality of images is quite severe. We consider the mean-square error (MSE) cost function and derive an expression for an unbiased estimate of the MSE. The resulting multiplicative noise unbiased risk estimator is referred to as MURE. The denoising operation is performed in the wavelet domain by considering the image-domain MURE. The parameters of the denoising function (typically, a shrinkage of wavelet coefficients) are optimized for by minimizing MURE. We show that MURE is accurate and close to the oracle MSE. This makes MURE-based image denoising reliable and on par with oracle-MSE-based estimates. Analogous to the other popular risk estimation approaches developed for additive, Poisson, and chi-squared noise degradations, the proposed approach does not assume any prior on the underlying noise-free image. We report denoising results for various noise levels and show that the quality of denoising obtained is on par with the oracle result and better than that obtained using some state-of-the-art denoisers.