A Local Nonlinear Model for the Approximation and Identification of a Class of Systems

Koeppl,

doi:10.1109/tcsii.2009.2015383

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Note the similarity of Eq. 9 with the Volterra kernels obtained by several authors [31][32][33] for bilinear systems in the input (that is, containing solely linear terms with respect to the input u(t)).…”

Section: Iiia Linearized-frequency Domain Methods For a Second Ordermentioning

confidence: 99%

An input-independent method for solving weakly nonlinear partial differential equations in the frequency domain: application to the Euler equations

Quero

2019

AIAA Aviation 2019 Forum

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In this work a novel approach in determining the first and second order frequencydomain Volterra kernels for weakly nonlinear partial differential equations (PDEs) in semidiscrete form based on the application of the harmonic probing (HP) method is presented. This represents a formal extension of the linearized-frequency domain (LFD) methods to a nonlinear framework, leading to a so-called LFD2 method. The method allows for the representation of weak nonlinearities by solving two input-independent linear algebraic systems of equations in the frequency domain and thus circumvents the solution of the nonlinear PDE by numerical integration for each different input, representing a nonlinear reduced-order model (ROM) for the physical phenomena. The general form of the equations is derived and an application to the well known viscous Burgers' equation to show its suitability in representing the nonlinear convective term is shown. Next, an application to the compressible quasi one-dimensional unsteady flow described by the Euler equations is presented. The proposed method overcomes two constraints present in other methods for the solution of nonlinear PDEs, namely, the consideration of exclusively periodic solutions as in the harmonic balance (HB) method and the dependency of the kernels with the input signal as in the Volterra kernel identification methods.

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Section: Iiia Linearized-frequency Domain Methods For a Second Ordermentioning

confidence: 99%

An input-independent method for solving weakly nonlinear partial differential equations in the frequency domain: application to the Euler equations

Quero

2019

AIAA Aviation 2019 Forum

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“…Therefore, MNT's inverse model must be accurate enough for authorized user to decrypt receipted signals. Now let's discuss whether classical memory nonlinear models, such as Volterra model [21], Hammerstein model [22], are suitable for designing MNT. Asymmetric Volterra model is expressed as…”

Section: Structure Of Nonlinear Transformation Pairmentioning

confidence: 99%

A Low Probability of Interception Method Based on Nonlinear Transformation of Channel Transmission Characteristic

Zhang¹,

Li²,

Tang³

et al. 2022

ACC

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To realize the low probability of interception communication system, this paper presents a memory nonlinear model to carry on nonlinear transformation for channel transmission characteristic. When primary signals are transmitted through this kind of system, the quality of signals will be observably deteriorated due to strong memory effect nonlinear distortion. Located at the frequency range where primary signals are, the nonlinearities decrease primary signals' signal to interference ratio (SIR) and memory effect introduce inter-symbol interference (ISI). Hence, with the purpose of encryption, the proposed model is designed to change both amplitude-frequency and phase-frequency characteristics in channel. At receiving end, suffered from bad SIR and ISI, illegal user cannot obtain correct information by I/Q demodulation and sample sentence processing, while authorized users can easily recover the primary signals waveform by proposed inverse nonlinear transformation model and get correct information next. The experiment results are provided to verify encryption effect of our method and analyze the loss of signal to noise ratio (SNR) of authorized user is also discussed for evaluating the impact of encryption method on conventional communication process.

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Laguerre-volterra model and architecture for MIMO system identification and output prediction

Yao

Chan

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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A generalized mathematical model is proposed for behaviors prediction of biological causal systems with multiple inputs and multiple outputs (MIMO). The system properties are represented by a set of model parameters, which can be derived with random input stimuli probing it. The system calculates predicted outputs based on the estimated parameters and its novel inputs. An efficient hardware architecture is established for this mathematical model and its circuitry has been implemented using the field-programmable gate arrays (FPGAs). This architecture is scalable and its functionality has been validated by using experimental data gathered from real-world measurement.

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A Local Nonlinear Model for the Approximation and Identification of a Class of Systems

Cited by 4 publications

References 13 publications

An input-independent method for solving weakly nonlinear partial differential equations in the frequency domain: application to the Euler equations

An input-independent method for solving weakly nonlinear partial differential equations in the frequency domain: application to the Euler equations

A Low Probability of Interception Method Based on Nonlinear Transformation of Channel Transmission Characteristic

Laguerre-volterra model and architecture for MIMO system identification and output prediction

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