High-speed, medium-resolution, analog-to-digital converters (ADCs) are important building blocks in a wide range of applications. High-speed, medium-resolution ADCs have been implemented by various ADC architectures such as a folding ADC, a subranging ADC, and a pipeline ADC. Among them, pipeline ADCs have proven to be efficient architectures for applications such as digital communication systems, data acquisition systems and video systems. Especially, power dissipation is a primary concern in applications requiring portability. Thus, the objective of this work is to design and build a low-voltage low-power medium-resolution (8-10bits) high-speed pipeline ADC in deep sub-micron CMOS technology. The non-idealities of the circuit realization are carefully investigated in order to identify the circuit requirements for a low power circuit design of a pipeline ADC. The resolution per stage plays an important role in determining overall power dissipation of a pipeline ADC. The pros and cons of both large and small number of bits per-stage are examined. A power optimization algorithm is developed to decide more accurately which approach is better for lower power dissipation. Both identical and non-identical number of bit per-stage approaches are considered and their differences are analyzed. A low-power, low-voltage 10-bit 100Msamples/s pipeline ADC was designed and implemented in a 0.18mm CMOS process. The power consumption was minimized with the right selection of the per-stage resolution based on the result of the power optimization algorithm and by the scaling down the sampling capacitor size in subsequent stages.

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This work lays out the development of a reconfigurable electronic system, which is composed of biologically relevant circuits. This system has been termed a Field-Programmable Neuron Array (FPNA) and is analogous to the more familiar Field-Programmable Gate Array (FPGA) and Field-Programmable Analog Array (FPAA). At the core of the system is an array of output somas based on previously developed bio-physically based channel models. Linking them together is a complex 2D dendrite matrix, FPAA-like floating-gate routing, and associated support circuitry. Several levels of generality give this system unprecedented re-configurability. The dendrite matrix can be arbitrarily configured so that many different topologies of dendrites can be investigated. Different soma circuits can be connected / disconnected to / from the dendrite matrix. Outputs from the somas can be arbitrarily routed to input synapses that exist at each dendrite node as well as the soma nodes. Lastly, the dynamics of each node consist of a mixture of individually tunable parts and global biases. All of this can be configured in concert to investigate neural circuits that exist in biological systems. This chip will have a significant impact on research in many fields including neuroscience, neuromorphic engineering, and robotics. This chip will allow for rapid prototyping of spinal circuits. Since the fundamental circuits of the system are chosen to be biologically relevant, outputs from the various nodes should also be relevant, thus yielding itself to use by neuroscientists. This system also provides a tool by where biological systems can be emulated in real-world electronic systems. Solutions to many problems faced by roboticists (such as bi-pedal standing / walking / running / jumping / climbing and the transitions between states) are present in biology. By providing a chip that can duplicate the same neural circuits that are responsible for these processes in the biology, the hypothesis is that researchers can begin to solve some of the same types of problems in artificial systems.

No description available.

Marroquin and Ramirez (1990) have recently discovered a class of discrete stochastic cellular automata with Gibbsian invariant measures that have a non-reversible dynamic behavior. Practical applications include more powerful algorithms than the Metropolis algorithm to compute MRF models. In this paper we describe a large class of stochastic dynamical systems that has a Gibbs asymptotic distribution but does not satisfy reversibility. We characterize sufficient properties of a sub-class of stochastic differential equations in terms of the associated Fokker-Planck equation for the existence of an asymptotic probability distribution in the system of coordinates which is given. Practical implications include VLSI analog circuits to compute coupled MRF models.

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada / This paper describes the design and calibration of a four-channel, airborne, swept-tuned spectrum analyzer used in two hypersonic flight experiments for characterizing dynamic data up to 25 kHz. Built mainly from commercially available analog function modules, the analyzer proved useful for an application with limited telemetry bandwidth, physical weight and volume, and electrical power. The authors discuss considerations that affect the frequency and amplitude calibrations, limitations of the design, and example flight data.

Volterra Series (VS) is often used in the analysis of mildly nonlinear circuits. In this approach, nonlinear circuit analysis is converted into the analysis of a series of linear circuits. The main benefit of this approach is that linear circuit analysis is well established and direct frequency domain analysis of a nonlinear circuit becomes possible. Sensitivity analysis is useful in comparing the quality of two designs and the evaluation of gradient, Jacobian or Hessian matrices, in analog Computer Aided Design. This thesis presents, for the first time, the sensitivity analysis of mildly nonlinear circuits in the frequency domain as an extension of the VS approach. To overcome efficiency limitation due to multiple mixing effects, Nonlinear Transfer Matrix (NTM) is introduced. It is the first explicit analytical representation of the complicated multiple mixing effects. The application of NTM in sensitivity analysis is capable of two orders of magnitude speedup. Per-element distortion decomposition determines the contribution towards the total distortion from an individual nonlinearity. It is useful in design optimization, symbolic simplification and nonlinear model reduction. In this thesis, a numerical distortion decomposition technique is introduced which combines the insight of traditional symbolic analysis with the numerical advantages of SPICE like simulators. The use of NTM leads to an efficient implementation. The proposed method greatly extends the size of the circuit and the complexity of the transistor model over what previous approaches could handle. For example, industry standard compact model, such as BSIM3V3 [35] was used for the first time in distortion analysis. The decomposition can be achieved at device, transistor and block level, all with device level accuracy. The theories have been implemented in a computer program and validated on examples. The proposed methods will leverage the performance of present VS based distortion analysis to the next level.

In this report we describe an adaptive simulated annealing method for sizing the devices in analog circuits. The motivation for use an adaptive simulated annealing method for analog circuit design are to increase the efficiency of the design circuit. To demonstrate the functionality and the performance of the approach, an operational transconductance amplifier is simulated. The circuit is modeled with symbolic equations that are derived automatically by a simulator.

Switching power converters are an indispensable part of every battery-operated consumer electronic product, nourishing regulated voltages to various subsystems. In these circuits, sensing the inductor current is not only necessary for protection and control but also is critical to be done in a lossless and accurate fashion for state-of-the-art advanced control techniques, which are devised to optimize transient response, increase the efficiency over a wide range of loads, eliminate off-chip compensation networks, and integrate the power inductor. However, unavailability of a universal, integrable, lossless, and accurate current-sensing technique impedes the realization of those advanced techniques and limit their applications. Unfortunately, use of a conventional series sense resistor is not recommended in high-performance, high-power switching regulators where more than 90% efficiency is required because of their high current levels. A handful of lossless current-sensing techniques are available but their accuracies are significantly lower than the traditional sense resistor scheme. Among available lossless but not accurate techniques, an off-chip, filter-based method that uses a tuned filter across the inductor to estimate current flow and its accuracy is dependent on the inductance and its equivalent series resistance (ESR) was selected for improvement because of its inherent continuous and low-noise operation. A schemes is proposed to adapt the filter technique for integration by automatically adjusting bandwidth and gain of an on-chip programmable gm-C filter to the off-chip power inductor during the system start-up through measuring the inductance and its ESR with on-chip generated test currents. The IC prototype in AMI s 0.5-um CMOS process achieved overall DC and AC gain errors of 8% and 9%, respectively, at 0.8 A DC load and 0.2 A ripple currents for inductors from 4 uH-14 uH and ESR from 48 mOhm to 384 mOhm when lossless, state-of-the-art schemes achieve 20 40% error and only when the nominal specifications of power component (power MOSFET or inductor) are known. Moreover, the proposed circuit improved the efficiency of a test bed current-mode controlled switching regulator by more than 2.6% at 0.8 A load compared to the traditional sense resistor technique with a 50 mOhm sense resistor.

<p>In this report we describe an adaptive simulated annealing method for sizing the devices in analog circuits. The motivation for use an adaptive simulated annealing method for analog circuit design are to increase the efficiency of the design circuit. To demonstrate the functionality and the performance of the approach, an operational transconductance amplifier is simulated. The circuit is modeled with symbolic equations that are derived automatically by a simulator.</p>