# q-Gaussian integrable Hamiltonian reductions in anisentropic gasdynamics

@article{Rogers2014qGaussianIH, title={q-Gaussian integrable Hamiltonian reductions in anisentropic gasdynamics}, author={Colin Rogers and Tommaso Ruggeri}, journal={Discrete and Continuous Dynamical Systems-series B}, year={2014}, volume={19}, pages={2297-2312} }

Integrable reductions in non-isothermal spatial gasdynamics are isolated corresponding to q-Gaussian density distributions. The availability of a Tsallis parameter q in the reductions permits the construction via a Madelung transformation of wave packet solutions of a class of associated q-logarithmic nonlinear Schrodinger equations involving a de Broglie-Bohm quantum potential term.

## 7 Citations

Reciprocal gausson phenomena in a Korteweg capillarity system

- Mathematics, PhysicsMeccanica
- 2019

In previous work in the literature, a kinetic derivation of a logarithmic nonlinear Schrodinger equation incorporating a de Broglie–Bohm term has been obtained in a capillarity context. Here,…

On Madelung systems in nonlinear optics: A reciprocal invariance

- Physics
- 2018

The role of the de Broglie-Bohm potential, originally established as central to Bohmian quantum mechanics, is examined for two canonical Madelung systems in nonlinear optics. In a seminal case, a…

Robust Adaptive Filtering under Least q-Gaussian Kernel Mean p-Power Error Criterion

- Computer Science2018 IEEE International Conference on Information Communication and Signal Processing (ICICSP)
- 2018

A recursive KAF algorithm, named as recursive least q-Gaussian kernel mean p- power (RQKMP), is derived under the LQK MP criterion for robust learning in noisy environment, which reveals superior performance against large outliers.

Robust Adaptive Filtering With $q$ -Gaussian Kernel Mean $p$-Power Error

- Computer ScienceIEEE Signal Processing Letters
- 2018

A new proposed algorithm reveals superior performance against Gaussian-type noise as well as the non-Gaussian perturbation, especially when the data contain large outliers.

Robust Adaptive Filtering With <inline-formula><tex-math notation="LaTeX">$q$</tex-math></inline-formula> -Gaussian Kernel Mean <inline-formula><tex-math notation="LaTeX">$p$</tex-math></inline-formula>-Power Error

- Computer ScienceIEEE Signal Processing Letters
- 2018

A novel information theoretic measure derived under the least QKMPE criterion for robust learning in noisy environment reveals superior performance against Gaussian-type noise as well as the non-Gaussian perturbation, especially when the data contain large outliers.

Interval Arithmetic based Adaptive Filtering Technique for Removal of Noise in Audio Signal

- EngineeringInternational Journal of Recent Technology and Engineering
- 2020

Active noise cancellation is one of the fundamental problems in acoustic signal processing. The proposed work focuses on the enhancement of audio signal quality by cancelling the noise using interval…

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