TIPS and the VIX: Spillovers from Financial Panic to Breakeven Inflation in an Automated, Nonlinear Modeling Framework

2017 ◽  
Vol 80 (2) ◽  
pp. 218-235 ◽  
Author(s):  
Josh R. Stillwagon
2012 ◽  
Vol 107 (12) ◽  
pp. 3296-3307 ◽  
Author(s):  
Nadja Schinkel-Bielefeld ◽  
Stephen V. David ◽  
Shihab A. Shamma ◽  
Daniel A. Butts

Intracellular studies have revealed the importance of cotuned excitatory and inhibitory inputs to neurons in auditory cortex, but typical spectrotemporal receptive field models of neuronal processing cannot account for this overlapping tuning. Here, we apply a new nonlinear modeling framework to extracellular data recorded from primary auditory cortex (A1) that enables us to explore how the interplay of excitation and inhibition contributes to the processing of complex natural sounds. The resulting description produces more accurate predictions of observed spike trains than the linear spectrotemporal model, and the properties of excitation and inhibition inferred by the model are furthermore consistent with previous intracellular observations. It can also describe several nonlinear properties of A1 that are not captured by linear models, including intensity tuning and selectivity to sound onsets and offsets. These results thus offer a broader picture of the computational role of excitation and inhibition in A1 and support the hypothesis that their interactions play an important role in the processing of natural auditory stimuli.


Author(s):  
Paul Miles ◽  
Graham Pash ◽  
William Oates ◽  
Ralph C. Smith

Dielectric elastomers are employed on a wide variety of adaptive structures. Many of these soft elastomers exhibit significant rate-dependencies in their response. Accurately quantifying this viscoelastic behavior is non-trivial and in many instances a nonlinear modeling framework is required. Fractional-order operators have been applied to modeling viscoelastic behavior for many years, and recent research has shown fractional-order methods to be effective for nonlinear frameworks. This implementation can become computationally expensive to achieve an accurate approximation of the fractional-order derivative. In this paper, we demonstrate the effectiveness of using quadrature techniques in approximating the Riemann-Liouville definition for fractional derivatives in the context of developing a nonlinear viscoelastic model.


Author(s):  
Saeid Bashash ◽  
Nader Jalili

Piezoelectric actuators with their sub-nanometer resolution and fast frequency response are becoming increasingly important in today’s micro-and nano-positioning technology. Along this line, this paper undertakes the development of a nonlinear modeling, system identification and control framework for piezoelectric actuators used in such positioning systems. More specifically, a general nonlinear modeling framework for a single piezoelectric actuator combined with a novel method for describing its hysteretic nonlinearity is proposed. For the actuator generated force, a polynomial form of the nonlinearity is assumed, and the time-varying history-dependent parameters of this polynomial are identified through the observed hysteretic characteristics of the actuator. Experimental results demonstrates the validity of the proposed the modeling and identification framework for an in-house high resolution piezoelectric-based stager with capacitive position sensor. Utilizing Lyapunov method and the sliding mode control strategy, the control force acting on the actuator is then designed such that the high frequency tracking control and the asymptotic stability of the system are attained. Simulation results indicate that controller suppresses the high frequency tracking error significantly, noticeably improving the tracking performance.


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