BIST/Digital-Compatible Testing of RF Devices Using Distortion Model Fitting

Testing of Radio Frequency (RF) circuits for nonlinearity specifications generally requires the use of multiple test measurements thereby contributing to increased test cost. Prior RF test methods have suffered from significant test calibration effort (training for supervised learners) when using compact tests or from increased test time due to direct specification measurement. On the other hand, due to aggressive technology scaling, there are plenty of digital transistors available that can be used to simplify testing of Analog/Mixed-Signal (AMS) and RF devices. In this paper, an RF test methodology is developed that: (a) allows RF devices to be tested for several distortion specifications using distortion model fitting algorithms in test time comparable to what can be achieved using supervised learning techniques while retaining the accuracy of direct specification measurement, (b) allows multiple RF specifications to be determined concurrently from a single data acquisition and (c) allows digital-compatible testing/BIST to be performed using digital testers or on-chip built in self-test (BIST) circuitry. With regard to (a), a key benefit is that no training of supervised learning algorithm is necessary. The proposed method based on distortion model fitting is shown to give excellent results across common RF performance metrics while providing ~10× improvements in test time compared to previous methods.     

Affine-structure-based facial image encoding

A real-time algorithm for affine-structure-based video compression for facial images is presented. The face undergoing motion is segmented and triangulated to yield a set of control points. The set of control points generated by triangulation are tracked across a few frames using an intensity-based correlation technique. For accurate motion and structure estimation a Kalman-filter-based algorithm is used to track features on the facial image. The structure information of the control points is transmitted only during the bootstrapping stage. After that only the motion information is transmitted to the decoder. This reduces the number of motion parameters associated with control points in each frame. The local motion of the eyes and lips is captured using local 2-D affine transformations. For real time implementation a quad-tree based search technique is adopted to solve local correlation. Any remaining reconstruction error is accounted for using predictive encoding. Results on real image sequences demonstrate the applicability of the method     

Clustering-Based Denoising With Locally Learned Dictionaries

In this paper, we propose K-LLD: a patch-based, locally adaptive denoising method based on clustering the given noisy image into regions of similar geometric structure. In order to effectively perform such clustering, we employ as features the local weight functions derived from our earlier work on steering kernel regression . These weights are exceedingly informative and robust in conveying reliable local structural information about the image even in the presence of significant amounts of noise. Next, we model each region (or cluster)-which may not be spatially contiguous-by ldquolearningrdquo a best basis describing the patches within that cluster using principal components analysis. This learned basis (or ldquodictionaryrdquo) is then employed to optimally estimate the underlying pixel values using a kernel regression framework. An iterated version of the proposed algorithm is also presented which leads to further performance enhancements. We also introduce a novel mechanism for optimally choosing the local patch size for each cluster using Stein's unbiased risk estimator (SURE). We illustrate the overall algorithm's capabilities with several examples. These indicate that the proposed method appears to be competitive with some of the most recently published state of the art denoising methods.     

A novel DSP‐based PFC‐DPLL with fuzzy controlled acquisition aid to improve acquisition performance and noise immunity

This paper proposes a new digital signal processing (DSP)‐based phase frequency controlled digital phase locked loop. Here, a very simplistic form of fuzzy logic controller with the help of carrier phase and frequency error as input data is used to provide an acquisition aid. A frequency discriminator is employed to generate frequency error, and phase detector output is taken for phase error. This addition of an acquisition aid helps the loop to achieve the minimum acquisition time and maximum noise rejection simultaneously. An additional phase control in the digitally controlled oscillator makes the loop perform even better towards this goal. The implementation of the proposed loop is carried out on a reconfigurable logic platform using System Generator^®;, a tool from Xilinx^®; used to design real‐time DSP application. A significant improvement of time domain characteristics are observed as well as the performance in presence of additive white Gaussian noise is demonstrated in terms of the reduction in steady‐state phase jitter and enhancement in output signal to noise ratio in the proposed loop. Copyright © 2014 John Wiley & Sons, Ltd.     

Elimination of truncation and round off error and enhancement of stability using a new split loop DPLL

In contrast with the conventional split loop digital phase lock loop, a new loop is presented in this paper that differs from the earlier version principally by design aspects. It incorporates an additional phase modulation input along with its frequency modulation input in the digital controlled oscillator. It is capable of eliminating the deleterious effects of rounding and truncation error with faster signal accusation. Higher loop stability is also achievable using the new split loop digital phase lock loop. Furthermore, radio frequency filtering is done using an In phase and Quadrature phase (IQ) voltage controlled oscillator to avoid interaction between the loop filter and the radio frequency filter. Copyright © 2011 John Wiley & Sons, Ltd.     

Modeling the drain current and its equation parameters for lightly doped symmetrical double-gate MOSFETs

A 2D model for the potential distribution in silicon film is derived for a symmetrical double gate MOSFET in weak inversion. This 2D potential distribution model is used to analytically derive an expression for the subthreshold slope and threshold voltage. A drain current model for lightly doped symmetrical DG MOSFETs is then presented by considering weak and strong inversion regions including short channel effects, series source to drain resistance and channel length modulation parameters. These derived models are compared with the simulation results of the SILVACO (Atlas) tool for different channel lengths and silicon film thicknesses. Lastly, the effect of the fixed oxide charge on the drain current model has been studied through simulation. It is observed that the obtained analytical models of symmetrical double gate MOSFETs are in good agreement with the simulated results for a channel length to silicon film thickness ratio greater than or equal to 2.     

Minimization in variations of different parameters in different φ planes of a small-size concentric ring array antenna using firefly algorithm

The radiation pattern of a small-size concentric ring array antenna does not remain φ-symmetric, if the array is made with an appreciably lesser number of antenna elements. The sidelobe level, first null beamwidth (FNBW), half-power beamwidth (HPBW), and the null depths of the radiation pattern change significantly in different φ planes. An efficient pattern synthesis method has been developed in this work to reduce the variation of sidelobe level, FNBW, and HPBW of a small-size concentric ring array of isotropic antennas, for different φ cuts. It is done by finding out an optimum set of amplitude distribution of the array elements using firefly algorithm. The sidelobe level and the first null depth of the array are kept below a desired value for all the defined φ cuts. The directivity of the optimized array and the uniform array has been computed. The variation of all these parameters for different φ cuts has been compared to the same array with uniform excitation among the elements.     

Single‐Walled Carbon Nanotube Dispersions in Poly(ethylene oxide)

Dispersions of single‐walled carbon nanotubes (SWNTs) in poly(ethylene oxide) (PEO) assisted by a lithium‐based anionic surfactant demonstrate an electrical percolation of 0.03 wt.‐% and a geometrical percolation, inferred from melt rheometry, of 0.09 wt.‐%. Both the melting temperature and the extent of crystallinity of the PEO crystals decrease with increasing SWNT loading. Raman spectroscopy of the nanocomposites indicates a down‐shift of the SWNT G‐modes and suggests that the nanotubes are subjected to tensile stress transfer from the polymer at room temperature.     

Molecular Dynamics Simulation of MBE Growth of CdTe/ZnTe/Si

We simulate in three dimensions molecular beam epitaxial (MBE) growth of CdTe/ZnTe/Si using classical molecular dynamics. Atomic interactions are simulated with Stillinger–Weber potentials, whose parameters are obtained by fitting to experimental data or density function theory-calculated distortion energies of the component crystals. The effects of substrate temperature and atomic species flux ratios on epilayer morphology are investigated. The agreement between simulations and experiments suggests that this model has reasonable ability to predict the microstructures of CdTe/ZnTe/Si grown by MBE.