Richard B. Wells

Hardware and software considerations for implementing hardware-in-the loop traffic simulation

Digital computer simulation provides an important tool for the study of complex systems. When the complexity of the problem is too large to warrant an analytical solution, simulation is the only option to analyze system configurations or operational modes prior to their implementation in the field. Not all components in a complex system can be modelled in adequate detail in computer simulations: for example, only simple, generic models of traffic controllers are available. Real-time hardware-in-the-loop simulation allows real traffic controllers to interact with computer simulations to improve accuracy. This paper provides an overview of real-time simulation and then discusses hardware and software constraints to implementing a controller interface device (the NIATT CID II) for real-time hardware-in-the-loop simulation.

A printer model using signal processing techniques

An accurate printer model that is efficient enough to be used by halftoning algorithms is proposed. The proposed signal processing model (SPM) utilizes a physical model to train adaptive linear combiners (ALCs), after which the average exposure of each subpixel for any input pattern can be calculated using the optimized weight vector. The SPM can be used to model multi-level halftoning and resolution enhancement, as well as traditional halftoning. The SPM is comprised of a single ALC layer followed by a peak-to-average ratio (PAR) correction layer, which serves to produce a PAR of less than 1.5 in the modeled exposure. The PCN (PAR correction network) employs one ALC/pixel and exploits the physics governing the characteristics of exposure in small regions. A relatively small number of training patterns suffices to train the SPM.

Estimation of the shape of magnetic transitions by a deconvolution technique

The measurement of magnetic transitions in a digital recording system through the application of digital signal processing is presented. The observability of the magnetization waveform in the presence of uncertainties in the readback parameters of the head is discussed. The effect of noise on the deconvolution process and algorithmic techniques for minimizing the resulting measurement errors are outlined. Finally the measurement is demonstrated for an experimental head/disk system. A procedure for inferring the dead layer depth in a Mn-Zn head is discussed and the measured M(x) is compared with some popular models.

Measurement of microbial activity in soil by colorimetric observation of in situ dye reduction: an approach to detection of extraterrestrial life

BackgroundDetecting microbial life in extraterrestrial locations is a goal of space exploration because of ecological and health concerns about possible contamination of other planets with earthly organisms, and vice versa. Previously we suggested a method for life detection based on the fact that living entities require a continual input of energy accessed through coupled oxidations and reductions (an electron transport chain). We demonstrated using earthly soils that the identification of extracted components of electron transport chains is useful for remote detection of a chemical signature of life. The instrument package developed used supercritical carbon dioxide for soil extraction, followed by chromatography or electrophoresis to separate extracted compounds, with final detection by voltammetry and tandem mass-spectrometry.ResultsHere we used Earth-derived soils to develop a related life detection system based on direct observation of a biological redox signature. We measured the ability of soil microbial communities to reduce artificial electron acceptors. Living organisms in pure culture and those naturally found in soil were shown to reduce 2,3-dichlorophenol indophenol (DCIP) and the tetrazolium dye 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide inner salt (XTT). Uninoculated or sterilized controls did not reduce the dyes. A soil from Antarctica that was determined by chemical signature and DNA analysis to be sterile also did not reduce the dyes.ConclusionObservation of dye reduction, supplemented with extraction and identification of only a few specific signature redox-active biochemicals such as porphyrins or quinones, provides a simplified means to detect a signature of life in the soils of other planets or their moons.

Stochastic optimization of a biologically plausible spino-neuromuscular system model

Simulations and modeling techniques are becoming increasingly important in understanding the behavior of biological systems. Detailed models help researchers answer questions in diverse areas such as the behavior of bacteria and viruses and aiding in the diagnosis and treatment of injuries and diseases. However, to yield meaningful biological behavior, biological simulations often include hundreds of parameters that correspond to biological components and characteristics. This paper demonstrates the effectiveness of genetic algorithms (GA) and particle swarm optimizer (PSO) based techniques in training biologically plausible behavior in a neuromuscular simulation of a biceps/triceps pair. The results are compared to human subjects during flexion/extension movements to show that these algorithms are effective in training biologically plausible behaviors on both neural and gross anatomical levels. Specific behaviors of interest that emerge include tonic tensions in both muscles during resting periods, biceps/triceps coactivation patterns, and recruitment-like behaviors. These are all fundamental characteristics of biological motor control and emerge without direct selection for these behaviors. This is the first time that all of these characteristic behaviors emerge in a model of this detail without direct selective pressure.

Doppler shift cancellation using phasor and split phasor LMS algorithms

Two adaptive algorithms for estimating and correcting Doppler shift in coherent M-ary phase shift keying (MPSK) receiver are discussed. By compensating the error in the phase domain a 1-tap phasor least mean square (LMS) algorithm and a 1-tap split phasor LMS algorithm are developed. The structures of the algorithms are very simple. The algorithms operate in a decision directed mode. Monte Carlo simulations results show that the proposed algorithms converge in a few symbols and are very attractive for real time signal processing and hardware implementation. It is shown that the 1-tap split phasor LMS algorithm is an unbiased estimator. On the other hand, the 1-tap phasor LMS is a biased estimator; its steady state and tracking misadjustment is also discussed.

Model order reduction for optimal bounding ellipsoid channel models

This paper presents a new algorithm for performing model order reduction for Volterra series channel models of high-density digital magnetic recording channels. We employ a set-membership approach to the problem in which a set of consistent modeling solutions bounded by an optimal ellipsoid is first developed for the channel. We then present a new algorithm for finding the minimum number of coefficients in the Volterra series expansion which preserves the accuracy, in a least-squares sense, of the reduced order model in comparison with the original model.

A multi-level DRAM with fast read and low power consumption

In this paper, we present a new, multi-level DRAM design, which can store 3 voltage levels (0, Vcc, and Vcc/2) in a single memory cell. This multi-level DRAM requires no special reference voltage and simplifies design of the peripheral circuits. Coding algorithms may be used to provide binary data immediately after first read, with the second read operation providing a second data word from the same cell; thus, binary data from two logical addresses can be obtained from one physical location. One of the coding algorithms uses an additional coding memory cell for every two data memory cells to provide 4-bits of binary data. A second algorithm uses 3 additional coding cells for every 8 data cells to provide 8-bit binary data for each access; thus every 11 memory cells can provide 16 bits of binary data. Furthermore, the read speed is faster than a conventional DRAM because the first access can complete before the word line reaches Vccp, and because a SRAM differential sense amplifier is used. Finally, storing 3 voltage levels in a single memory cell also reduces average power consumption, since the Vcc/2 voltage level requires less write back current than 0 or Vcc voltage level

Phase and amplitude jitter cancellation using 1-step LMS linear predictor

The use of a 1-step least mean square (LMS) linear predictor for sinusoidal phase and amplitude jitter cancellation is considered in the paper. The structure of the algorithm is very simple; it is very attractive for real time signal processing and hardware implementation. The use of ellipse eccentricity epsiv as a figure of merit (FOM) for the degree of cancellation is discussed in the paper. A phenomenon of amplitude modulation to phase modulation (AM-to-PM) conversion is characterized and analyzed. The performance of the algorithm over an additive white Gaussian noise channel is studied by simulations.

Delay-resistor implementation of integrators in biomimic artificial neurons

This paper presents an approach to leaky integrator implementation in biomimic artificial neurons. In this implementation, the delay inherent in MOSFET devices due to their parasitic capacitance is used in place of explicit capacitors to obtain a leaky integrator function. The resulting circuit realizes a nonlinear integrator with differing integration risetimes and falltimes. The MOSFET resistors are operated in the triode region. We discuss how such issues as gate bias levels and input/output signal swings affect the dynamic response of the integrator.