Scattering theory and linear optimal control: Regulator and servo problems

In this paper, several known computational solutions are readily obtained in a very natural way for the linear regulator, fixed end-point and servo-mechanism problems using a certain frame-work from scattering theory. The relationships between the solutions to the linear regulator problem with different terminal costs and the interplay between the forward and backward equations have enabled a concise derivation of the partitioned equations, the forward-backward equations, and Chandrasekhar equations for the problem. These methods have been extended to the fixed end-point, servo, and tracking problems.

An Area-Efficient Noise-Adaptive Neural Amplifier in 130 nm CMOS Technology

Chronic recording of neural signals is indispensable in designing efficient brain–machine interfaces and to elucidate human neurophysiology. The advent of multichannel micro-electrode arrays has driven the need for electronics to record neural signals from many neurons. The dynamic range of the system can vary over time due to change in electrode–neuron distance and background noise. We propose a neural amplifier in UMC 130 nm, 1P8M complementary metal–oxide–semiconductor (CMOS) technology. It can be biased adaptively from 200 nA to 2 $mu{rm A}$, modulating input referred noise from 9.92 $mu{rm V}$ to 3.9 $mu{rm V}$. We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. Optimum sizing of the input transistors minimizes the accentuation of the input referred noise of the amplifier and obviates the need of large input capacitance. The amplifier achieves a noise efficiency factor of 2.58. The amplifier can pass signal from 5 Hz to 7 kHz and the bandwidth of the amplifier can be tuned for rejecting low field potentials (LFP) and power line interference. The amplifier achieves a mid-band voltage gain of 37 dB. In vitro experiments are performed to validate the applicability of the neural low noise amplifier in neural recording systems.

A PPCA based non-parametric modeling and retrieval of PD signal buried in excessive noise

The problem of on-line recognition and retrieval of relatively weak industrial signals such as partial discharges (PD), buried in excessive noise, has been addressed in this paper. The major bottleneck being the recognition and suppression of stochastic pulsive interference (PI) due to the overlapping broad band frequency spectrum of PI and PD pulses. Therefore, on-line, onsite, PD measurement is hardly possible in conventional frequency based DSP techniques. The observed PD signal is modeled as a linear combination of systematic and random components employing probabilistic principal component analysis (PPCA) and the pdf of the underlying stochastic process is obtained. The PD/PI pulses are assumed as the mean of the process and modeled instituting non-parametric methods, based on smooth FIR filters, and a maximum aposteriori probability (MAP) procedure employed therein, to estimate the filter coefficients. The classification of the pulses is undertaken using a simple PCA classifier. The methods proposed by the authors were found to be effective in automatic retrieval of PD pulses completely rejecting PI.

Evolution of 1/f α noise during electromigration stressing of metal film: Spectral signature of electromigration process

In this paper we report a systematic study of low-frequency 1/fα resistance fluctuation in a metal film at different stages of electromigration. The resistance fluctuation (noise) measurement was carried out in presence of a dc electromigration stressing current. We observe that in addition to the increase in the spectral power SV(f), the frequency dependence of the spectral power changes as the electromigration process progresses and the exponent α starts to change from 1 to higher value closer to 1.5. We interpret this change in α as arising due to an additional contribution to the spectral power with a 1/f3/2 component, which starts to contribute as the electromigration process progresses. This additional component SV(f) ∼ 1/f3/2 has been suggested to originate from long range diffusion that would accompany any electromigration process. The experimental observation finds support in a model simulation, where we also find that the enhancement of noise during electromigration stressing is accompanied by a change in spectral power frequency dependence.

Effect of gate-drain/source overlap on the noise in 90 nm N-channel metal oxide semiconductor field effect transistors

In this paper, we have studied the effect of gate-drain/source overlap (LOV) on the drain channel noise and induced gate current noise (SIg) in 90 nm N-channel metal oxide semiconductor field effect transistors using process and device simulations. As the change in overlap affects the gate tunneling leakage current, its effect on shot noise component of SIg has been taken into consideration. It has been shown that “control over LOV” allows us to get better noise performance from the device, i.e., it allows us to reduce noise figure, for a given leakage current constraint. LOV in the range of 0–10 nm is recommended for the 90 nm gate length transistors, in order to get the best performance in radio frequency applications.

Study of symmetrical and related components through the theory of linear vector spaces

The paper proposes a study of symmetrical and related components, based on the theory of linear vector spaces. Using the concept of equivalence, the transformation matrixes of Clarke, Kimbark, Concordia, Boyajian and Koga are shown to be column equivalent to Fortescue's symmetrical-component transformation matrix. With a constraint on power, criteria are presented for the choice of bases for voltage and current vector spaces. In particular, it is shown that, for power invariance, either the same orthonormal (self-reciprocal) basis must be chosen for both voltage and current vector spaces, or the basis of one must be chosen to be reciprocal to that of the other. The original �¿, ��, 0 components of Clarke are modified to achieve power invariance. For machine analysis, it is shown that invariant transformations lead to reciprocal mutual inductances between the equivalent circuits. The relative merits of the various components are discussed.