Minimax estimation of deterministic parameters in linear models with a random model matrix

We consider the problem of estimating an unknown deterministic parameter vector in a linear model with a random model matrix, with known second-order statistics. We first seek the linear estimator that minimizes the worst-case mean-squared error (MSE) across all parameter vectors whose (possibly weighted) norm is bounded above. We show that the minimax MSE estimator can be found by solving a semidefinite programming problem and develop necessary and sufficient optimality conditions on the minimax MSE estimator. Using these conditions, we derive closed-form expressions for the minimax MSE estimator in some special cases. We then demonstrate, through examples, that the minimax MSE estimator can improve the performance over both a Baysian approach and a least-squares method. We then consider the case in which the norm of the parameter vector is also bounded below. Since the minimax MSE approach cannot account for a nonzero lower bound, we consider, in this case, a minimax regret method in which we seek the estimator that minimizes the worst-case difference between the MSE attainable using a linear estimator that does not know the parameter vector, and the optimal MSE attained using a linear estimator that knows the parameter vector. For analytical tractability, we restrict our attention to the scalar case and develop a closed-form expression for the minimax regret estimator.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

The First Template‐Free Growth of Crystalline Silicon Microtubes

A simple template‐free high‐temperature evaporation method was developed for the growth of crystalline Si microtubes for the first time. As‐grown Si microtubes were characterized using X‐ray diffraction, scanning electron microscopy, transmission electron microscopy, and room‐temperature photoluminescence. The lengths of the Si tubes can reach several hundreds of micrometers; some of them have lengths on the order of millimeters. Each tube has a uniform outer diameter along its entire length, and the typical outer diameter is ≈ 2–3 μm. Most of the tubes have a wall thickness of ≈ 400–500 nm, though a considerable number of them exhibit a very thin wall thickness of ≈ 50 nm. Room‐temperature photoluminescence measurement shows the as‐synthesized Si microtubes have two strong emission peaks centered at ≈ 589 nm and ≈ 617 nm and a weak emission peak centered at ≈ 455 nm. A possible mechanism for the formation of these Si tubes is proposed. We believe that the present discovery of the crystalline Si microtubes will promote further experimental studies on their physical properties and smart applications.     

An improved statistical analysis of the least mean fourth (LMF) adaptive algorithm

The paper presents an improved statistical analysis of the least mean fourth (LMF) adaptive algorithm behavior for a stationary Gaussian input. The analysis improves previous results in that higher order moments of the weight error vector are not neglected and that it is not restricted to a specific noise distribution. The analysis is based on the independence theory and assumes reasonably slow learning and a large number of adaptive filter coefficients. A new analytical model is derived, which is able to predict the algorithm behavior accurately, both during transient and in steady-state, for small step sizes and long impulse responses. The new model is valid for any zero-mean symmetric noise density function and for any signal-to-noise ratio (SNR). Computer simulations illustrate the accuracy of the new model in predicting the algorithm behavior in several different situations.     

High-performance MIM capacitor using ALD high-k HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectrics

For the first time, we successfully fabricated and demonstrated high performance metal-insulator-metal (MIM) capacitors with HfO/sub 2/-Al/sub 2/O/sub 3/ laminate dielectric using atomic layer deposition (ALD) technique. Our data indicates that the laminate MIM capacitor can provide high capacitance density of 12.8 fF//spl mu/m/sup 2/ from 10 kHz up to 20 GHz, very low leakage current of 3.2 /spl times/ 10/sup -8/ A/cm/sup 2/ at 3.3 V, small linear voltage coefficient of capacitance of 240 ppm/V together with quadratic one of 1830 ppm/V/sup 2/, temperature coefficient of capacitance of 182 ppm//spl deg/C, and high breakdown field of /spl sim/6 MV/cm as well as promising reliability. As a result, the HfO/sub 2/-Al/sub 2/O/sub 3/ laminate is a very promising candidate for next generation MIM capacitor for radio frequency and mixed signal integrated circuit applications.     

Near-ML multiuser detection with linear filters and reliability-based processing

The prohibitive - exponential in the number of users - computational complexity of the maximum-likelihood multiuser detector for direct-sequence code-division multiple-access communications has fueled an extensive research effort for the development of low-complexity multiuser detection alternatives. We show that we can efficiently and effectively approach the error rate performance of the optimum multiuser detector as follows. We utilize a multiuser zero-forcing or minimum mean-square error (MMSE) linear filter as a preprocessor and we establish that the output magnitudes, when properly scaled, provide a reliability measure for each user bit decision. Then, we prepare an ordered, reliability-based error search sequence of length linear in the number of users; it returns the most likely user bit vector among all visited options. Numerical and simulation studies for moderately loaded systems that permit exact implementation of the optimum detector indicate that the error rate performance of the optimum and the proposed detector are nearly indistinguishable over the whole predetection. signal-to-noise ratio range of practical interest. Similar studies for higher user loads (that prohibit comparisons with the optimum detector) demonstrate error rate performance gains of orders of magnitude in comparison with straight decorrelating or MMSE multiuser detection.     

Analysis of feedback for higher order polarization-mode dispersion mitigation of NRZ 40-Gb/s optical transmission

First-order polarization-mode dispersion (PMD) compensation by means of a polarization controller and a differential delay line is not sufficient to guarantee error-free transmission for 40-Gb/s channels when higher order effects severely increase signal distortion. Higher order mitigation is possible by cascading more than one first-order block. However, only two-stage or three-stage devices remain simple enough to be actually controlled. The performance of such higher order PMD compensators is evaluated by means of numerical simulations. Two different feedback signals have been used, demonstrating that first-order and higher order PMD distortion of nonreturn-to-zero (NRZ) pulses at 40 Gb/s can be strongly mitigated for instantaneous values of the differential group delay (DGD) up to the bit slot, when the compensator is properly controlled.     

Pseudorandom active UWB reflectors for accurate ranging

In this letter, the concept of pseudorandom active reflector, based on the ultra-wideband (UWB) technology, is introduced. It consists of a simple device that repeats a slightly delayed version of the received UWB signal only in certain time intervals according to a suitable pseudorandom time-hopping sequence. An example of application of this device for accurate ranging in precise location systems is given. The advantages of this solution are in the hardware simplicity (only the analog section is present), in the low power consumption of the reflector and in the low timing constraint regarding the relative transmitter and reflector clock rates.     

Hf-doped and NH/sub 3/-nitrided high-K gate dielectric thin film with least drain current degradation and flatband voltage shift

A novel technique to form high-K dielectric of HfSiON by doping base oxide with Hf and nitridation with NH/sub 3/, sequentially, is proposed. The HfSiON gate dielectric demonstrates excellent device performances such as only 10% degradation of saturation drain current and almost 45 times of magnitude reduction in gate leakage compared with conventional SiO/sub 2/ gate at the approximately same equivalent oxide thickness. Additionally, negligible flatband voltage shift is achieved with this technique. Time-dependent dielectric breakdown tests indicate that the lifetime of HfSiON is longer than 10 years at V/sub dd/=2 V.