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Simulation Of Microwave And MillimeterWave Oscillators, Present Capability And Future Directions
 Proc. Workshop on Integrated Nonlinear Microwave and Millimeterwave Circuits
, 1992
"... The current stateofthe art of oscillator simulation techniques is presented. Candidate approaches for the next genertion of oscillator simulation techniques are reviewed. The method is presented which uses an e#cient and robust convolutionbased procedure to integrate frequencydomain modeling of ..."
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The current stateofthe art of oscillator simulation techniques is presented. Candidate approaches for the next genertion of oscillator simulation techniques are reviewed. The method is presented which uses an e#cient and robust convolutionbased procedure to integrate frequencydomain modeling of a distributed linear network in transient simulation. The impulse response of the entire linear distributed network is obtained and the algorithm presented herein ensures that aliasing e#ects are minimized by introducing a procedure that ensures that the interconnect network response is both timelimited and bandlimited. In particular, artificial filtering to bandlimit the response is not required. I. Introduction Large signal simulation of microwave oscillators is necessary to provide steadystate characterization of oscillator performance. Such quantities as power and harmonic content information are then readily available. This is particularly important in achieving first pass successf...
High Order Volterra Series Analysis Using Parallel Computing
"... INTRODUCTION The Volterra series technique has been used extensively in various applications in the area of nonlinear circuit analysis and optimization (see e.g. references [1][28]). Examples are in the (i) analysis of intermodulation in small signal amplifiers [6][12], (ii) determination of os ..."
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INTRODUCTION The Volterra series technique has been used extensively in various applications in the area of nonlinear circuit analysis and optimization (see e.g. references [1][28]). Examples are in the (i) analysis of intermodulation in small signal amplifiers [6][12], (ii) determination of oscillation frequency and amplitude in near sinusoidal oscillators [3][5], (iii) analysis of mixers with moderate local oscillator levels [13, 14], analysis of communication systems [14][18], and (v) analysis of noise in nonlinear networks [24][28]. The use of the Volterra series technique basically involves two steps: (i) first, from specified input signal frequencies to determine all relevant Volterra transfer functions of the network, and (ii) next, to determine the output response from the nonlinear network based on specified amplitudes of the input signals. One limitation in the use of Volterra series is that the determination of Volterra transfer functions is usually limi
The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems
, 1993
"... LUNSFORD II, PHILIP J. The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems. (Under the direction of Michael B. Steer.) A new technique for the frequencydomain behavioral modeling and simulation of nonautonomous nonlinear analog subsystems is presented. ..."
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LUNSFORD II, PHILIP J. The Frequency Domain Behavioral Modeling and Simulation of Nonlinear Analog Circuits and Systems. (Under the direction of Michael B. Steer.) A new technique for the frequencydomain behavioral modeling and simulation of nonautonomous nonlinear analog subsystems is presented. This technique extracts values of the Volterra nonlinear transfer functions and stores these values in binary files. Using these files, the modeled substem can be simulated for an arbitrary periodic input expressed as a finite sum of sines and cosines. Furthermore, the extraction can be based on any circuit simulator that is capable of steady state simulation. Thus a large system can be divided into smaller subsystems, each of which is characterized by circuit level simulations or lab measurements. The total system can then be simulated using the subsystem characterization stored as tables in binary files.