Novel mixture model–based approaches for person verification using multimodal biometrics

With growing concerns about security, the world over, biometric-based person verification is gaining more and more attention. Recently, multimodal biometric has attracted increasing focus among researchers as this overwhelms many limitations of unimodal biometric systems and hence more reliable. In this paper, we propose four different feature extraction techniques namely Principle Component Analysis Mixture Model (PCA MM), Singular Value Decomposition Mixture Model (SVD MM), Independent Component Analysis I Mixture Model (ICA I MM), and Independent Component Analysis II Mixture Model (ICA II MM) to design a multimodal biometric system at feature level. The proposed methods begin with modeling the multimodal biometrics data using Gaussian Mixture Model followed by a subspace methods like PCA, SVD, ICA I, and ICA II. Extensive experiments are carried out to observe the verification performance of the proposed methods at feature and match score level on large dataset of 150 users. We compare the results of the combined biometric with the results of individual biometric and also results of the proposed schemes against conventional (without mixture model) subspace approaches. The experimental results demonstrate the effectiveness of the proposed methods in designing a robust multimodal biometric system for accurate person verification.     

Extracting single dispersion Cole–Cole impedance model parameters using an integrator setup

In this letter, we report an integrator-based setup to extract the four parameters that characterize a single-dispersion Cole–Cole impedance model without direct measurement of the complex impedance. Experimental results in the range 100 Hz–1 MHz using apple and plumb fruits are given and results are compared with numerical simulations of the acquired model.     

Hysteresis modeling and tracking control for a dual pneumatic artificial muscle system using Prandtl–Ishlinskii model

This study investigated pressure/length hysteresis characteristics. Instead of the conventional force/length hysteresis model, a Prandtl–Ishlinskii (P–I) model of a dual pneumatic artificial muscle (PAM) system is presented. For the comparison, an alternative hysteresis model such as Bouc–Wen (B–W) model is also considered. All model parameters are identified by real code genetic algorithm (RCGA). Different feedback control strategies are combined with a feed-forward controller based on a P–I model for hysteresis compensation to reduce the tracking error of the dual PAM system. The experimental results validated the use of the proposed controller for trajectory tracking of PAM systems.     

An automatic procedure for the synthesis and optimization of very low-frequency Gm–C integrators

Fully integrated low frequency filters are critical cells that should be carefully designed in order to avoid excessive area occupation. In this work we propose an automatic procedure capable of optimizing the design of G_m?CC integrators, which constitute the basis of a wide class of G_m?CC filters. The optimization target is minimizing the cell area with constraints on input range and low frequency noise. Lower and upper bounds can be fixed to most quantities and design parameters in order to avoid solutions that are not compatible with the physical limitations of the process. The program has been developed within the MATLAB^? platform, exploiting the optimization toolbox. The effect of several important design parameters on the optimization of low frequency integrators has been investigated using the proposed routine. The strong interaction between noise and low frequency constraints has been demonstrated, showing the impressive impact of strict noise specifications on the occupied area. The actual effectiveness of parameters such as the current division factor or approaches such as flicker noise rejection by means of chopper modulation has been investigated. Examples of integrator synthesis, performed using the proposed procedure configured with the parameters of a commercial CMOS process, are presented. The consistence between the characteristics of the cells and the initial specifications has been checked using electrical simulations showing a maximum discrepancy with the initial specifications of nearly 80%. A semi-manual method to refine the synthesized cells and improve the accuracy is proposed.     

Low area ASIC implementation of LUT–CLA–QTL architecture for cryptography applications

Wireless Networks - The block cipher (BC) algorithm is very fast and easy to standardize and facilitate the hardware (H/W) and software implementations. Thus, in data security BC values are the...     

Deep CNN model for crops’ diseases detection using leaf images

Multidimensional Systems and Signal Processing - The agricultural yield of any country provides the base for the development of that nation. Sustainable growth needs to maintain crop production up...     

Mixed analog-digital crossbar-based hardware implementation of sign–sign LMS adaptive filter

Recently announcement of a physical realization of a fundamental circuit element called memristor by researchers at Hewlett Packard (HP) has attracted so much interest worldwide. Combination of this newly found element with crossbar interconnect technology, opened a new field in designing configurable or programmable electronic systems which can have applications in signal processing and artificial intelligence. In this paper, based on the simple memristor crossbar structure, we will propose a new mixed analog-digital circuit as a hardware implementation of the sign–sign least mean square (LMS) adaptive filter algorithm. In this proposed hardware, any multiplication and addition is performed with infinite precision and there is no necessity for the quantization of the input signal. Since the coefficients of the filter are stored in the switches of the crossbar, they can remain unchanged theoretically for an infinite period of time.     

Bulk-tuned Gm–C filter using current cancellation

A new approach for small transconductance (Gm) OTA designs, suitable for relatively low frequency filtering applications in the range of few kHz, is proposed. Small Gm values are achieved by a current cancellation technique, and are adjustable by bulk driving the MOS transistors of the input differential amplifier. The OTA design procedure takes into account Pelgrom׳s modeling of mismatch errors. A common-mode feedback control circuit based on floating gate common-mode voltage detector that shares the filter main capacitances is also presented. Experimental results obtained with a low-pass filter with tunable cutoff frequency implemented in a 0.35 μm CMOS process to verify the effectiveness of the design procedure have shown close agreement with the theory.     

Design and implementation of a switched capacitor-based embedded hybrid DC–DC converter

The binary coded form of minterms for both minterms and reduced minterms is used in a very simple method for searching for prime implicants of logic functions. It only requires XOR and comparison operations.     

Realistic model of compact VLSI FitzHugh–Nagumo oscillators

In this article, we present a compact analogue VLSI implementation of the FitzHugh–Nagumo neuron model, intended to model large-scale, biologically plausible, oscillator networks. As the model requires a series resistor and a parallel capacitor with the inductor, which is the most complex part of the design, it is possible to greatly simplify the active inductor implementation compared to other implementations of this device as typically found in filters by allowing appreciable, but well modelled, nonidealities. We model and obtain the parameters of the inductor nonideal model as an inductance in series with a parasitic resistor and a second order low-pass filter with a large cut-off frequency. Post-layout simulations for a CMOS 0.35 μm double-poly technology using the MOSFET Spice BSIM3v3 model confirm the proper behaviour of the design.     

The system modelling and circuit implementation from time–frequency domain signal specifications

The system modelling and the circuit implementation of the nonlinear circuits using the wavelet domain techniques has been accomplished in this study. When the time–frequency domain specifications have been given as the wavelet ridges, the signal with the given ridges has been synthesized. Then, the dynamical wavelet network has been trained for the synthesized signal. The circuit of the wavelet network has been designed and simulated.     

Interface states model for III–V oxide interfaces

A general model of the density of interface states at III–V oxide interfaces is presented. The interface states arise from the native defects, such as Ga or As dangling bonds and Ga–Ga or As–As like-atom bonds created by oxidation. As–As bonds are a likely cause of states at the conduction band edge of GaAs. The model explains the difficulty of n-type operation for GaAs FETs compared to GaAs pFETs or to InGaAs nFETs.     

A model and framework for human–environment interaction

This paper describes our approach for studying and prototyping human–environment interaction (HEI) within a pervasive space applied to ambient assistive living context. The objective of our approach consists in developing and implementing an HEI framework to modelling the human–machine interaction. This framework allows a customization facility for designers, developers and even end-users in defining and processing multimodal interaction. We underline the fact that the design of interaction for users with special needs do not have to be considered as orthogonal to the application but rather as a validation context which is the heart of our research laboratory activities. We have integrated our framework in demonstrator dedicated to people with disabilities to validate the concept. This paper will present the framework, the developed components of our HEI model and the prototype realised. The outcome of this research activity is to provide a multimodal processing framework to favour natural human pervasive environment by decreasing the cognitive workload necessary in a complex environment. Thus, this will contribute to achieve ubiquitous accessible space.     

Depth and depth–color coding using shape-adaptive wavelets

We present a novel depth and depth–color codec aimed at free-viewpoint 3D-TV. The proposed codec uses a shape-adaptive wavelet transform and an explicit encoding of the locations of major depth edges. Unlike the standard wavelet transform, the shape-adaptive transform generates small wavelet coefficients along depth edges, which greatly reduces the bits required to represent the data. The wavelet transform is implemented by shape-adaptive lifting, which enables fast computations and perfect reconstruction. We derive a simple extension of typical boundary extrapolation methods for lifting schemes to obtain as many vanishing moments near boundaries as away from them. We also develop a novel rate-constrained edge detection algorithm, which integrates the idea of significance bitplanes into the Canny edge detector. Together with a simple chain code, it provides an efficient way to extract and encode edges. Experimental results on synthetic and real data confirm the effectiveness of the proposed codec, with PSNR gains of more than 5 dB for depth images and significantly better visual quality for synthesized novel view images.     

Fast block implementation of two-dimensional FIR digital filters via the Walsh–Hadamard decomposition

The block implementation of two-dimensional finite-impulse response (FIR) digital filters is considered using the matrix decomposition approach. The coefficient matrix of the block realization is decomposed via the Walsh-Hadamard transform without involving any intermediate calculations. The resulting structure is modular, regular, has high inherent parallelism and may be easily pipelined so that it may be implemented via very large scale integration array processors.     

Design and implementation of adaptive slope compensation in current mode DC–DC onverter

To improve the compensation for the inherent instability in a current mode converter, the adaptive slope compensation, giving attention to the problems of the traditional compensation on compensation accuracy, loading capability and turning jitter, is presented. Based on the analysis of current loop, by detecting the input and output voltage, converting the adaptive slope compensation current, the compensation of the current loop is optimized successfully. It can not only improve the compensation accuracy but also eliminate the over compensation, the turning jitter and the poor loading capability in the reported slope compensation. A power supply chip with adaptive slope compensation has been fabricated in a 0.35 μm CMOS process. The measurement results show that the chip starts up and operates steadily with the constant current limit under conditions of 5 V input voltage, from 10% to 100% duty cycle.     

Engineering the current–voltage characteristics of metal–insulator–metal diodes using double-insulator tunnel barriers

The femtosecond-fast transport in metal–insulator–metal (MIM) tunnel diodes makes them attractive for applications such as ultra-high frequency rectenna detectors and solar cells, and mixers. These applications impose severe requirements on the diode current–voltage I(V) characteristics. For example, rectennas operating at terahertz or higher frequencies require diodes to have low resistance and adequate nonlinearity. To analyze and design MIM diodes with the desired characteristics, we developed a simulator based on the transfer-matrix method, and verified its accuracy by comparing simulated I(V) characteristics with those measured in MIM diodes that we fabricated by sputtering, and also with simulations based on the quantum transmitting boundary method. Single-insulator low-resistance diodes are not sufficiently nonlinear for efficient rectennas. Multi-insulator diodes can be engineered to provide both low resistance and substantial nonlinearity. The improved performance of multi-insulator diodes can result from either resonant tunneling or a step change in tunneling distance with voltage, either of which can be made to dominate by the appropriate choice of insulators and barrier thicknesses. The stability of the interfaces in the MIIM diodes is confirmed through a thermodynamic analysis.     

Bias-dependent hybrid PKI empirical–neural model of microwave FETs

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical–neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.     

A contactless power transfer system using a series–series–parallel resonant converter

In this article, a contactless power transfer system using a series–series–parallel resonant converter (SSPRC) is proposed. The proposed converter can improve on or eliminate the disadvantages of the contactless system based on conventional resonant converters, since it independently compensates for a primary side leakage inductance, a secondary side leakage inductance and a magnetising inductance. The proposed converter also reduces the circulating currents and the reactive power by controlling the phase angle difference between the inverter output voltage and the current. In addition, the system design can be simplified, since the voltage gain is determined only by the transformer turns ratio for the overall load range without being affected by the other transformer parameters. The proposed converter is analysed with respect to the gain and current margin. The system design procedure is then described for the proposed circuit based on the circuit analysis. Finally, the experimental results are presented in order to verify the proposed contactless power supply.     

Efficient facial landmark localization using spatial–contextual AdaBoost algorithm

Facial landmark detectors can be categorized into global and local detectors. Global facial landmark detectors rely on global statistical relations between landmarks, but do not sufficiently utilize local appearance information, whereas local detectors mainly focus on local appearance attributes of landmarks. Although the AdaBoost algorithm has been successfully employed in object localization, it cannot take advantage of geometric facial feature distribution very well. We propose an AdaBoost algorithm called SC-AdaBoost, which efficiently combines the global knowledge of landmark distribution, the regional shape model, and the local landmark attributes based on a coarse-to-fine strategy. The global prior distribution of landmarks is estimated using a face image set with landmark annotations. First, the face region is detected as a rectangular bounding box using a Haar-like feature-based boosting method, and the global distribution of landmarks is used to determine the facial component regions. Facial landmark localization is roughly performed by regional shape modeling. Posteriors of individual weak classifiers are determined by Gabor wavelet analysis at landmark candidate positions constrained by the regional shape model. SC-AdaBoost is established by empirical risk minimization, which decides the weights for the weak classifiers, and is used for the precise localization. The strength of the proposed approach is shown by extensive experiments using standard face datasets.