Sumona Mukhopadhyay

California Polytechnic State University, San Luis Obispo | Cal Poly

In this work, we try to address the two challenging problems in machine learning (ML) which are: (a) the need for large amounts of labeled images for training supervised classifiers and (b) the supervised classification for time series data. We formulate the problem as an image classification task by transforming time series into domain-specific 2D...

Microservice applications are increasingly embracing cloud platforms to run their services. These applications can often be impacted by anomalies. Detecting anomalies at runtime is vital to ensure that cloud-native applications meet specified requirements and ensure good Quality-of-Service. However, this is challenging to do since application owner...

Objective clinical tools, including cognitive-motor integration (CMI) tasks, have the potential to improve concussion rehabilitation by helping to determine whether or not a concussion has occurred. In order to be useful, however, an individual must put forth their best effort. In this study, we have proposed a novel method to detect the difference...

The unique properties of chaotic signals have led to their application in improving blind system identification performance. However, the role of chaos in blind identification of a sparse system has not been investigated. In this letter, we apply symbolic dynamics to encode a random signal to reap the benefits of chaos in improving blind identifica...

In this work we consider the problem of blind system identification in noise driven by an independent and identically distributed (i.i.d) non-Gaussian signal generated from a deterministic nonlinear chaotic system. A new estimator for the phase space volume (PSV) which is a dynamic-based property of chaos is derived using the maximum likelihood for...

The success of sensor based application depends on the availability of clean data and its fail safe operation. However, due to their inherent dynamical behavior, detecting faults in sensors can be challenging. To this end, we propose a signal processing and non-linear dynamics based fault detection approach for learning the normal/abnormal states o...

The problem of distinguishing deterministic chaos from non-chaotic dynamics has been an area of active research in time series analysis. Since noise contamination is unavoidable, it renders deterministic chaotic dynamics corrupted by noise to appear in close resemblance to stochastic dynamics. As a result, the problem of distinguishing noise-corrup...

The perception of color is an important cognitive feature of the human brain. The variety of colors that impinge upon the human eye can trigger changes in brain activity which can be captured using electroencephalography (EEG). In this work, we have designed a multiclass classification model to detect the primary colors from the features of raw EEG...

In this paper a chaos-based approach is proposed for system identification with binary random signal. A chaos-based approach is developed to model random binary sequence and is applied to blind system identification. The Cramér Rao Lower Bound (CRLB) based on the chaos representation is derived. The theoretical mean square error (MSE) of the propos...

The paper proposes a scheme for achieving steganography with multiple encrypted monochromatic images with keys obtained from a synchronized system of semiconductor lasers. The key selection scheme for steganography determines the robustness of the application. It is in this area that steganography may benefit from the properties of chaos synchroniz...

Bio-inspired robotics is an emerging field of cognitive intelligence which is based on the fundamental assumption that the biological systems are capable of self organization, better capable to adapt themselves to their changing environment for survival. Based on these features, behaviours observed in the biological world can be transferred to robo...

This work applies nonlinear dynamics to model the encoded time series describing human activities performed in the spatio-temporal domain. We augment the concepts of symbolic dynamics and formal language theory to pattern recognition in generating probabilistic feature extraction which are used to drive a Bayesian classifier for behavior recognitio...

A new technique of transmitting encrypted combinations of gray scaled and chromatic images using chaotic lasers derived from Maxwell–Bloch's equations has been proposed. This novel scheme utilizes the general method of solution of a set of linear equations to transmit similar sized heterogeneous images which are a combination of monochrome and chro...

The control and estimation of unknown parameters of chaotic systems are a daunting task till date from the perspective of nonlinear science. Inspired from ecological co-habitation, we propose a variant of Particle Swarm Optimization (PSO), known as Chaotic Multi Swarm Particle Swarm Optimization (CMS-PSO), by modifying the generic PSO with the help...

This work aims to demonstrate the effect of synchronization phenomena in chaotic laser systems described by modified Lang–Kobayashi's (L–K) delay differential equations. The synchronized system considered for numerical simulations and for cryptography consists of identical semiconductor lasers operating in single longitudinal mode. The two lasers a...

Robustness of cellular networks in case of handling faults still remains a daunting task. Mobile computing technology has rapidly become can indispensable mode in various e-commerce transactions along with voice and video communication. With these facilities comes the threat of security and integrity of information which are equally important to be...

Optical chaos is a topic of current research characterized by high-dimensional nonlinearity which is attributed to the delay-induced dynamics, high bandwidth and easy modular implementation of optical feedback. In light of these facts, which adds enough confusion and diffusion properties for secure communications, we explore the synchronization phe...

The Optical chaotic systems, with infinite dimensionality, have gained a lot of attention for communication and cryptographic purposes. The semiconductor devices act as a cryptosystem with high bandwidth. We explore the synchronization phenomenon between two spatio-temporal chaotic semi conductor lasers with bi-directional coupling. The coupling fa...

In this chapter, the authors have attempted to explore an association between chaos synchronization with genetic engineering algorithm. The authors developed a cryptographic technique using keys generated by time delayed synchronized systems by modifying the selection mechanism of the basic genetic algorithm. This has resulted into a proposed genet...

The control of nonlinear chaotic system and theestimation of parameters is a vital issue in nonlinear science.Studies on parameter estimation for chaotic systems have beeninvestigated recently. A variant of Particle Swarm Optimization(PSO) known as Chaotic Multi Swarm Particle SwarmOptimization (CMS-PSO) is proposed which is inspired fromthe metaph...