Digital Commons Network^™

Musical Objects, Territories, And Otherness, Andrew Farrar

LSU Doctoral Dissertations

As the materials that composers work with have become increasingly focused on elements outside traditional pitch relations such as timbre or register, so have their approaches to form. One such stream in modern composition, starting from electronic composers such as Pierre Schaeffer, is the use of ”sound” or ”musical” objects. These materials are marked by their wholistic nature, where qualities such as timbre, density, and con- tour are as important to their identity as pitch relationships. Composers such as Schaeffer, James Tenney, and Denis Smalley have all discussed these sound objects in their writings, though they refer to them under …

Statistical Evaluation Of A New Orleans Historic Rainfall Dataset (1840–1893), Arielle C. Filostrat

LSU Master's Theses

This study evaluates the climatic credibility of a newly identified historical rainfall dataset for New Orleans, Louisiana, spanning 1840–1893. The New Orleans Historical Dataset (NOHD) is compared to a modern observational record from the Audubon rain gauge (1893–2024) to determine whether nineteenth-century rainfall observations are consistent with known precipitation behavior in the region. Establishing the reliability of early records is critical for extending climatological baselines and improving understanding of long-term rainfall variability.

Historical rainfall observations were first evaluated through archival review using the New Orleans Medical and Surgical Journal and other nineteenth-century meteorological records to verify notable rainfall events. Daily …

A Stochastic Maximum Principle For Singular Mean-Field Regime-Switching Optimal Control, Maalvladedon Ganet Some, Edward Korveh

Journal of Stochastic Analysis

In this paper, we investigate a mean-field singular stochastic optimal control problem for systems governed by mean-field regime-switching singular stochastic differential equations. The state process is assumed to depend on both a regular and a singular control, and the coefficient associated with the singular component is allowed to be regime dependent. We derive both necessary and sufficient singular stochastic maximum principles. Because the regular control domain is not assumed to be convex, we employ the spike variation technique and obtain the necessary maximum principle by introducing a second-order adjoint process. As an application, we use the main theoretical results to …

Generalized Delayed Black–Scholes Formula, Bi Gole Hubert Le, Auguste Aman

Journal of Stochastic Analysis

The aim of this paper is to derive an explicit pricing formula for European options when the underlying asset follows a linear generalized delay differential equation in two distinct financial markets. The pricing methodology is based on the construction of an equivalent martingale measure using Girsanov’s theorem. Our models preserve both the no-arbitrage condition and market completeness. As such, this work extends the framework previously developed by Arriojas et al. in [16], providing a broader class of delay-based option pricing models.

Robust Optimal Consumption, Investment And Reinsurance For Recursive Preferences, Elizabeth Dadzie, Wilfried Kuissi Kamdem, Marcel Ndengo

Journal of Stochastic Analysis

This paper investigates a robust optimal consumption, investment, and reinsurance problem for an insurer with Epstein-Zin recursive preferences operating under model uncertainty. The insurer’s surplus follows the diffusion approximation of the Cramér-Lundberg model, and the insurer can purchase proportional reinsurance. Model ambiguity is characterised by a class of equivalent probability measures, and the insurer, being ambiguity-averse, aims to maximise utility under the worst-case scenario. By solving the associated coupled forward-backward stochastic differential equation (FBSDE), we derive closed-form solutions for the optimal strategies and the value function. Our analysis reveals how ambiguity aversion, risk aversion, and the elasticity of intertemporal substitution …

An Itô Integral For A Two-Sided Lévy Process, Raluca Balan, Jaime Garza

Journal of Stochastic Analysis

In this article, we construct an Itô integral with respect to a two-sided finite-variance Lévy process {L(x)}x∈R, without a Gaussian component. Using Rosenthal inequality for discrete-time martingales, we give an estimate for the p-th moment of this integral, for any even integer p ≥ 2. Then, using Poisson-Malliavin calculus, we show that the Itô integral is an extension of the Hitsuda-Skorokhod integral with respect to the compensated Poisson random measure associated to the Lévy process.

Supersymmetric Quantum Fields Via Quantum Probability, Radhakrishnan Balu

Journal of Stochastic Analysis

The super version of imprimitivity theorem is available now to describe global supersymmetry of systems using the representations of super Lie groups (SLG). This result uses the equivalence between super Harish- Chandra pairs and super Lie groups, at the categorical level, and is applicable to super Poincaré group and generalizes a smooth SI to super context. We apply the result to build supersymmetric quantum fields. Towards this end, we set up a super Fock space of a disjoint union of super Hilbert spaces which is equivalent to super tensoring of boson (even) part symmetrically and that of fermion (odd) part …

Convergence To Fractional Brownian Motion For Weighted Random Sums In Besov Space, Ibrahima Mendy

Journal of Stochastic Analysis

We consider infinite sums of weighted i.i.d. random variables, with finite variance and arbitrary distribution, and we derives conditions for the weak convergence in Besov space of normalized sums to fractional Brownian motion (fBm).

Pricing Variance Swaps Using Extended Heston Model, Semere Gebresilasie, Mulue Gebreslasie, Indranil Sengupta

Journal of Stochastic Analysis

Abstract. In this study, we introduce a variance swap for the underlying asset utilizing the Heston model, incorporating a long-term variance that is treated as a stochastic function of time. We develop a closed-form solution for the variance swap under this framework, where the log returns are driven by a compound Poisson process. Our analysis of historical data reveals that long-term variance is not constant; instead, it fluctuates over time, reflecting market dynamics more accurately. By integrating this time-varying long-term variance into the model, we achieve an improvement in prediction performance of approximately 60%. Furthermore, we perform model calibration using …

Understanding The Needs And Practices Of Cut Flower Growers In Louisiana, Jessie M. Hoover

LSU Doctoral Dissertations

The specialty cut flower industry is expanding nationwide, including southeastern states such as Louisiana. Existing studies and market analyses focus on national trends of other regions with established floriculture networks, leaving a critical gap in understanding the unique challenges and opportunities faced by growers in Louisiana. This lack of data limits the ability of extension professionals, policymakers, and industry stakeholders to develop targeted strategies that support local production and market development. This study used qualitative case study methods to investigate the practices, challenges, and needs of 13 specialty cut flower growers in Louisiana. The study utilized Urie Bronfenbrenner’s (1979, 1986) …

A Pedagogical Exploration Of Haydn's Early Keyboard Sonatas: No.7 In C Major, No.8 In G Major, And No.11 In G Major, Chun Ka Lam

LSU Doctoral Dissertations

This study examines the pedagogical exploration of Joseph Haydn’s early keyboard sonatas, Sonata No. 7 in C Major (Hob. XVI:7), Sonata No. 8 in G Major (Hob. XVI:8), and Sonata No. 11 in G Major (Hob. XVI:11). These Sonatas target intermediate-level piano students. In this study, I am going to explore Classical-era techniques, including articulation, phrasing, dynamic contrast, and ornamentation, which mainly focus on technical and musical challenges. This study highlights the development of important skills for more advanced repertoire.

Effects Of Peer Tutoring Training Duration And Group Piano Level On Harmonization And Transposition Achievement And Learning Attitudes Of Undergraduate Non-Keyboard Music Students, Jinnan Liu

LSU Doctoral Dissertations

The purpose of this study was to examine the relationships among peer tutoring training duration, group piano level, and undergraduate non-keyboard music students’ achievement in harmonization and transposition, as well as their learning attitude following peer tutoring. Based on the literature on cooperative learning, peer-assisted learning, and reciprocal peer tutoring, this study examined whether differences in training duration and group piano level were related to student performance and learning experiences in university group piano.

A quasi-experimental 2  2 design was used. The independent variables were peer tutoring training duration (2-day vs. 4-day) and group piano level (Group Piano II vs. …

Control Theories For Machine Learning Algorithms Analysis And Design (Ct4ml): An Overview Of A Short Course, Yangquan Chen

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Data-Driven Predictive Control For Uav Interception Via Koopman-Based Lifting, Sanjay Maharjan, Darren Johnson, Animesh Bangal, Yousuf Atteia, Tariq Hlayel, Adrian Stein

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Learning To Sample And Update In Mppi Control, Viet-Anh Le, Rahul Mangharam

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Soft Robotics And Sensor-Embedded Inferior Vena Cava Simulator, Robert Herbert, Julio Zuazola, Anish Maharjan, Tatum Dixon, Landon Hyder, Lily Nguyen

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Gain-Modulated Pid Control: A Framework For Sensitivity Shaping Under Parametric Uncertainty, Nyi Nyi Aung, Abigail Lawlor, Adrian Stein

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Robustness Of Gradient-Based Optimization Under Perturbations: From Deterministic To Stochastic Noise, Leilei Cui

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Fairness-Aware Management Of Electric Vehicle Charging Stations, Paulo Bessa Do Rego Monteiro, Ricardo Pinto De Castro

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Blood Pressure Prediction During Hemorrhage And Blood Transfusion: A Population-Informed Sequential Inference Approach, Yi-Ming Kao, Parham Rezaei, Sina Masoumi Shahrbabak, Jeremy Alanano Pepino, Ian Sebastian Kirk Shogren, Yang Wang, Andrew Tomas Reisner, Jin-Oh Hahn

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Identifiability, Observability, Parameter Reduction, And State Estimation For Nonsmooth Dynamical Systems, Hesham Abdelfattah, Peter Stechlinski, Sameh Eisa

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Dynamics-Informed Subset Selection For Nonlinear System Identification, Max Herkersdorf

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Positive Rewards Alone Enable Bipedal Standing For Unitree Go2 In Isaac Lab, Hamza Mustafa, Runjia Song, Wenlu Du

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Coupled Sensing And Path-Planning In Search And Rescue Missions, Prakash Poudel, Jeffrey Desroches, Raghvendra V. Cowlagi

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Morphquad: Morphable Quadrotor For Superhuman Maneuverability, Manipulation, And Resiliency, José Díaz Peón González Pacheco, Jiawei Xu Dr., Andrew Zhao, Hongyu Zhou, Atharva Navsalkar, Andrew Scheffer, Amrith Malli Reddi, Sashreek Shankar, Yuqing Ivan Bao, Vasileios Tzoumas Dr.

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

The General Polyak-Lojasiewicz Inequality And Its Connection To Neural Network Training, Arthur Castello B. De Oliveira, Eduardo Sontag

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Autonomy For Lunar Surface Infrastructure Construction, John Cooper, Irina Kostitsyna, Olivia Irene B. Formoso, Dominic Bisio, Joshua N. Moser, Matthew P. Vaughan, Joshua N. Moser, Matthew K. Mahlin

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Robust Mpc Design For Leaky-Integrator Echo State Networks, Hao Deng, Cristina Stoica, Daniel Ossmann, Mohammed Chadli

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Adaptive Dae Observer For Joint State And Parameter Estimation In Parallel-Connected Li-Ion Batteries With Experimental Validation, Jorge E. Espin, Dong Zhang

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Utilizing Impulsive Inputs For Identification Of Robot Inertial Parameters Without Acceleration Information, Nilay Kant

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.