Efficient encoding of facsimile using an adaptive technique

Two binary encoding schemes which lead to bandwidth and power saving are proposed. The binary source is encoded into digrams, which then undergo certain restrictions prior to transmission. Resultant ambiguity at the decoder is avoided by predictive feedback at the encoder. The specific examples proposed belong to a wide class of such adaptive encoding schemes.     

Efficient radar signature prediction using a frequency-aspectinterpolation technique based on adaptive feature extraction

A radar cross section (RCS) interpolation technique in both frequency and aspect is proposed for the efficient prediction of radar signatures from computational electromagnetics data. Our approach is based on a multiple-arrival model for the induced current on the target. The model parameters are determined by an adaptive feature extraction (AFE) algorithm, which uses an iterative search-and-extract procedure to find the individual model features. Random frequency and aspect sampling is used to circumvent the ambiguity in selecting the features. Numerical examples are presented to test the interpolation algorithm. It is found that sufficient accuracy in the predicted radar features can be achieved even when the original computed data is sampled at 5:1 below the Nyquist criterion in either frequency or aspect. The algorithm is also applied to efficiently predict the radar images of the benchmark VFY218 airplane at UHF band with good results     

Simultaneous transmission of speech and data using an adaptive cancelling technique

A new scheme to transmit data and analogue speech simultaneously over an analogue transmission line is presented. The transmitter simply combines speech and modulated voice-band data signals together while the receiver uses an adaptive cancelling technique to recover these signals from the received composite. The scheme works for phase-dispersive channels and without bandwidth expansion.     

A novel digital predistorter technique using an adaptive neuro-fuzzy inference system

This letter presents a novel digital predistorter technique using an adaptive neuro-fuzzy inference system (ANFIS). The proposed approach employs real-time input and output signals of a nonlinear power amplifier as inputs to the ANFIS, so as to approximate the inverse functions of the power amplifier. The antecedent and consequent parameters of the FIS constructed by the ANFIS are tuned using backpropagation and least squares algorithms. Simulation shows that this novel technique has improved the linearity of a WCDMA signal by a further 4 dBc compared to a conventional look-up table (secant) approach. Moreover, this proposed technique is capable of adapting to instantaneous variation in the power amplifier response through time, which is a topic often omitted by researchers in this area.     

A re-extrapolation technique in Newton-SOR computer simulation of semiconductor devices

A novel extrapolation technique which learns from the failure of previous linear extrapolation result and subsequently changes the extrapolation scale accordingly is found to be very useful in dealing with the divergence problem in Newton-Successive Over Relaxation (SOR) computer simulation of semiconductor devices. The algorithm and an example are described in this paper.     

Tamper video detection and localization using an adaptive segmentation and deep network technique

In this work we have explored the hybrid deep learning architecture for recognizing the tampering from the videos. This hybrid architecture explores the features from the authentic videos to categorize the tampered portions from the forged videos. Initially, the process begins by compressing the input video using the Discrete cosine transform (DCT) based double compression approach. Then, the filtering process is carried out to improve the quality of compressed frame using the bilateral filtering. Then, the modified segmentation approach is applied to segment the frames into different regions. The features from these segmented portions are extracted and fed into hybrid DNN-AGSO (deep neural network- Adaptivf RELATED WORKSe Galactic Swarm Optimization) using Gabor wavelet transform (GWT) technique. Three different datasets are used to evaluate the overall performance they are, VTD, MFC-18, and VIRAT by MATLAB platform. The recognition rate achieved by VTD, MFC-18, and VIRAT datasets are 96%, 95.2%, and 93.47% respectively.     

Modeling and simulation of photonic devices by generalized space mapping technique

The generalized space mapping (GSM) technique is employed for modeling and simulation of photonic devices. The mapping is established between the parameter spaces of coarse and fine models so that accuracy of the coarse model is significantly improved for a given range of parameters. To demonstrate the usefulness of this technique, modeling and simulation of an optical waveguide facet is used as an application example. Two methods are adopted for the coarse model, i.e., the transfer matrix method (TMM) and the free space radiation mode (FSRM) method. The time-intensive and accurate finite-difference time-domain (FDTD) method is used as the fine model for model calibration. The mapping-enhanced coarse models show significant improvement in terms of accuracy. Further, a criterion is established to measure the accuracy of the coarse models. It is shown that the FSRM is one order of magnitude more accurate than the TMM for the TE case, however, the two methods have almost the same level of accuracy for the TM case.     

Efficient simulation of switched networks using reduced unificationmatrix

A new and simple formulation method for switched networks in the numerical time domain is presented. Unification models of switching devices, companion models of energy-storage elements, and several straightforward circuit-manipulated operations are used in obtaining a reduced unification matrix (RUM). The feature of the constant formulated RUM is clarified, and the selection of the main parameters of unification models is illustrated. A condition of reducibility is proposed to determine how small the dimensions of a modified nodal matrix (MNM) can be reduced to. Simulation results using the RUM method demonstrate its superiority over the commonly used MMM method, not only for memory requirements, but also for computational speed. A large circuit example shows that the RUM method offers a 76.32% time savings in computation. Additionally, the RUM method possesses the merits of easy formulation, easy programming and more realistic switch modeling, as well as greater accuracy and higher time efficiency when compared with commonly used state-space approaches. These combined advantages should make the proposed RUM method very attractive in the time-domain simulation of switched networks. For large switched networks, the decided advantages are very great     

Network reliability evaluation of three-state devices using transformation technique

Equations for delta-star and star-delta transformations are derived for 3-state device networks. These equations are obtained by equating probability of failure for a pair of nodes of both delta and star network. A function minimization method is suggested to solve the nonlinear algebraic equations in case of the star-delta transformation.     

采用自适应调制技术的时变MIMO信道的性能分析

本文采用可变速率和功率的MQAM调制方式研究时变情况下多输入多输出（MIMO）系统的性能,推导出了在速率离散分阶的情况下的功率和速率的分配公式.对不同的速率量化算法的仿真实验表明,在不知道信道矩阵概率密度函数的情况下,本文采用的速率量化算法可以有效的提高系统的频谱利用率,同时大大的减小了计算的复杂性.     

一种改进型自适应A-MAC算法分析与仿真

无线传感器网络的MAC协议可以利用监听/睡眠周期节约能源。对监听/睡眠周期和网络性能的关系进行了分析,研究了自适应的MAC协议及改进算法,通过动态调整节点唤醒的周期和相位来适应网络的动态变化。仿真表明改进后的协议可以减少时延,提高吞吐量和能源效率。     

激光多普勒测量皮肤血流的Monte Carlo模拟

本文根据皮肤的双层模型,分别用两种相位函数给出光子与红血球碰撞的散射角,利用Monte carlo方法得出探测到的光子强度分布、光子数按频移的分布,以及总频移和平均频移与红血球浓度的关系。发现在低浓度时总频移与浓度呈线性,指出频移的强度涨落的一阶矩和带权重的一阶矩在低浓度时反映红血球的平均速率而在高浓度时反映均方根速率。     

A NEW APPROACH OF LADDER SIMULATION ACTIVE BANDPASS FILTER——USING COMPLEX SCALING AND NIC EMBEDDING

Here we present a new method of constructing ladder simulation filters using the complex scaling and negative immittance converter (NIC) embedding. This method saves the number of operational amplifiers, and thereby lowers the cost and power consumption. It also avoids floating elements, and is easy to adjust. It still acquires the merit of low sensitivity. The problem of error minimization and stability are also discussed.     

Design of an adaptive CRSN using OFDM

Wireless Networks - Cognitive Radio (CR) is a novel concept that enables wireless devices to detect and adapt to their surroundings in order to enhance communication quality. The cognitive radio...     

Efficient simulation of nonuniform transmission lines using integrated congruence transform

This paper presents a new algorithm based on integrated congruence transform for efficient simulation of nonuniform transmission lines. The proposed algorithm introduces the concept of model-order reduction (MOR) via implicit usage of the Hilbert-space moments in distributed networks. The key idea in the proposed algorithm is the development of an orthogonalization procedure that does not require the explicit computation of the Hilbert-space moments in order to find their spanning orthogonal basis. The proposed orthogonalization procedure can thus be used to compute an orthogonal basis for any set of elements that are related through a differential operator in a generalized Hilbert space, without the need to have these elements in an explicit form. The proposed algorithm also addresses the problem of MOR of nonuniform transmission lines, through defining a weighted inner product and norm mappings over the Hilbert space of the moments. Numerical examples demonstrate more accurate numerical approximation capabilities over using the moments explicitly.     

Computer simulation of transferred electron devices using the displaced Maxwellian approach

Computer simulations of GaAs transferred electron devices have been performed by solving the time- and space-dependent Boltzmann equation and assuming displaced Maxwellian distributions for the two conduction band valleys. Since this model includes particle, momentum, and energy relaxation (as distinct from models using instantaneous velocity field dependence) and retains the spatial dependence (as distinct from uniform field models) it is particularly well suited for studying cases that are characterized by a strong x-dependence of electron temperature. Short devices as well as long ones operating at very high frequencies have been studied extensively, since these devices were thought and, in fact, have been found to be strongly affected by nonuniform energy relaxation due to contacts, domains, and other types of space charge. The results have been compared with experimental findings and with theoretical results computed by others.     

Coded block neural network VLSI system using an adaptive learning-rate technique to train Chinese character patterns

A coded block neural network VLSI system is presented that uses an adaptive learning-rate technique to train Chinese character patterns. Using the adaptive learning-rate technique, 500 Chinese characters have been successfully trained in 47.2 h using a 28 MIPs computer.<>     

Design and simulation of an efficient adaptive delta modulationembedded coder

An embedded coding version of hybrid companding delta modulation (HCDM) is described that operates from 16 to 48 kb/s in 8 kb/s steps. The embedded HCDM coder employs the explicit noise coding technique to transmit an adaptive PCM (APCM) coded version of the HCDM reconstruction error signal as a supplementary bit stream that may be partly or wholly deleted in transmission. SNR performance with speech input depends critically on the design of the supplemental APCM code and two new coding algorithms are investigated. In algorithm 1, the basic cue for step size adaptation is obtained from the RMS slope energy of the HCDM output whereas in algorithm 2, the HCDM reconstruction error is logarithmically compressed before quantisation and the basic step size is derived from peak input magnitudes. Instantaneous adaptation for both algorithms is achieved by using step size multipliers which are optimised for operation at single fixed bit rates and also for decoding with an unknown number of input bit deletions. Simulation results show that SNR performance is significantly enhanced using either algorithm and a graceful reduction of reconstructed speech quality with progressive bit deletion is achieved over the range from 48 kb/s to 16 kb/s. On the whole, the SNR performance of the embedded HCDM system is superior in comparison with conventional HCDM     

Determination of an initial mesh for computer simulation of H-abrupt devices

A computer procedure to determine the initial potential distribution in the vicinity of semiconductor junction structures, in particular hyperabrupt ones, is outlined. The procedure has the advantage of cutting down on computation time, especially if high applied voltages are considered.     

Extending multiresolution time-domain (MRTD) technique to the simulation of high-frequency active devices

We present a new time-domain simulation approach for large-signal physical modeling of high-frequency semiconductor devices using wavelets. The proposed approach solves the complete hydrodynamic model, which describes the transport physics, on nonuniform self-adaptive grids. The nonuniform grids are obtained by applying wavelet transforms followed by hard thresholding. This allows forming fine and coarse grids in locations where variable solutions change rapidly and slowly, respectively. A general criterion is mathematically defined for grid updating within the simulation. In addition, an efficient thresholding formula is proposed and verified. The developed technique is validated by simulating a submicrometer FET. Different numerical examples are presented along with illustrative comparison graphs, showing over 75% reduction in CPU time, while maintaining the same degree of accuracy achieved using a uniform grid case. Tradeoffs between threshold values, CPU time, and accuracy are discussed. To our knowledge, this is the first time in the literature to implement and report a wavelet-based hydrodynamic model simulator. This study also represents a fundamental step toward applying wavelets to Maxwell's equations in conjunction with the hydrodynamic model for accurate modeling of high-frequency active devices aiming to reduce the simulation time, while maintaining the same degree of accuracy.