activity
20172026
collaborators

13 papers

eess.SY2026

Latent Safety Filters: When a Lossy Encoder Admits a Transferable Certificate

Johannes Mootz, Zahra Nili Ahmadabadi, Reza Akhavian

Latent safety filters certify safety on a learned low-dimensional representation of the state, enabling constraints that resist analytic description. Because the encoder is lossy,…

math.OC2026

Lyapunov Constructions for System Interconnections Arising from Adaptation in Some Optimization Methods

Qixu Wang, Patrick McNamee, Zahra Nili Ahmadabadi +1

Interconnected systems have been widely studied, with a focus on interconnected systems whose subsystems are solely input-to-state stable (ISS) or passive systems. The focus of thi…

eess.SY2026

Logarithmic Barrier Functions for Practically Safe Extremum Seeking Control

Qixu Wang, Patrick McNamee, Zahra Nili Ahmadabadi

This paper presents a methodology for Practically Safe Extremum Seeking (PSfES), designed to optimize unknown objective functions while strictly enforcing safety constraints via a…

math.OC2025

Extremum Seeking (ES) is Practically Stable Whenever Model-Based ES is Stable

Patrick McNamee, Zahra Nili Ahmadabadi, Mirslav Krstić

Extremum seeking controllers (ESCs) are optimization algorithms in continuous time, with model-based ESCs using true derivative information of the cost function and model-free ESCs…

math.OC2024

Adaptive Extremum Seeking Control via the RMSprop Optimizer

Patrick McNamee, Zahra Nili Ahmadabadi

Extremum Seeking Control (ESC) is a well-known set of continuous time algorithms for model-free optimization of a cost function. One issue for ESCs is the convergence rates of para…

math.OC2024

Extremum Seeking is Stable for Scalar Maps that are Strictly but Not Strongly Convex

Patrick McNamee, Miroslav Krstić, Zahra Nili Ahmadabadi

For a map that is strictly but not strongly convex, model-based gradient extremum seeking has an eigenvalue of zero at the extremum, i.e., it fails at exponential convergence. Inte…

cs.SD2023

Feature Aggregation in Joint Sound Classification and Localization Neural Networks

Brendan Healy, Patrick McNamee, Zahra Nili Ahmadabadi

This study addresses the application of deep learning techniques in joint sound signal classification and localization networks. Current state-of-the-art sound source localization…

cs.RO2023

Autonomous search of real-life environments combining dynamical system-based path planning and unsupervised learning

Uyiosa Philip Amadasun, Patrick McNamee, Zahra Nili Ahmadabadi +1

In recent years, advancements have been made towards the goal of using chaotic coverage path planners for autonomous search and traversal of spaces with limited environmental cues.…

math.DS2019

On proximal relations in transformation semigroups arising from generalized shifts

Fatemah Ayatollah Zadeh Shirazi, Amir Fallahpour, Mohammad Reza Mardanbeigi +1

For a finite discrete topological space with at least two elements, a nonempty set , and a map , with (for…

math.GT2017

Possible heights of graph transformation groups

Fatemah Ayatollah Zadeh Shirazi, Arezoo Hosseini, Zahra Nili Ahmadabadi

In the following text we prove that for all finite there exists a topological graph such that is the collection of all possible h…

math.DS2017

Set-theoretical entropies of generalized shifts

Zahra Nili Ahmadabadi, Fatemah Ayatollah Zadeh Shirazi

In the following text for arbitrary with at least two elements, nonempty set and self-map we prove the set-theoretical entropy of generalized shift $σ_φ:X^Γ\to X^…

math.DS2017

Distributional chaotic generalized shifts

Zahra Nili Ahmadabadi, Fatemah Ayatollah Zadeh Shirazi

Suppose is a finite discrete space with at least two elements, is a nonempty countable set, and consider self--map . We prove that the generalized shift $σ_φ:X^Γ\t…

math.DS2017

Specification properties on uniform spaces

Fatemah Ayatollah Zadeh Shirazi, Zahra Nili Ahmadabadi, Bahman Taherkhani +1

In the following text we introduce specification property (stroboscopical property) for dynamical systems on uniform space. We focus on two classes of dynamical systems: generalize…