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Author

A. Emre Cetin

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10 papers indexed here

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#edge computing Open access Sep 2026

Real-Time Aerodynamic Flow Reconstruction from Ultra-Sparse Sensors via Deep Permutation Networks (DPN) and Idempotent Physical Projections

Real-time estimation of full unsteady aerodynamic flow fields $\mathbf{u}(\mathbf{x}, t) = (u, v)$ from ultra-sparse discrete sensor observations (e.g., $M \le 10$ point velocity probes across thousands of grid cells) is a foundational challenge in active flow control, wind tunnel telemetry, and unmanned aerial vehicle...

A. Emre Cetin · 0 citations
#edge computing Open access Sep 2026

Deep Permutation Networks: Layerwise Invariant Manifolds, Closed-Form Attractor Splicing, and Zero-Backpropagation Topological Learning

For four decades, deep artificial neural networks have relied on continuous vector spaces, dense floating-point General Matrix Multiplications (GEMM: hl+1 = σ(Wlhl + bl)), and gradient-based backpropagation. While effective in data centers, this paradigm incurs severe thermodynamic, memory bandwidth, and numerical stab...

A. Emre Cetin · 0 citations
#edge computing Open access Sep 2026

Deep Permutation Networks: Layerwise Invariant Manifolds, Closed-Form Attractor Splicing, and Zero-Backpropagation Topological Learning

For four decades, deep artificial neural networks have relied on continuous vector spaces, dense floating-point General Matrix Multiplications (GEMM: hl+1 = σ(Wlhl + bl)), and gradient-based backpropagation. While effective in data centers, this paradigm incurs severe thermodynamic, memory bandwidth, and numerical stab...

A. Emre Cetin · 0 citations
#diffusion models Open access Sep 2026

Deterministic Electrochemical Battery State Estimation via Volume-Weighted Lithium Mass Hyperplane Projections: Achieving Zero-Drift SoC and Hard Real-Time BMS on Microcontrollers

Precise on-board estimation of State of Charge (SoC) and State of Health (SoH) in lithium-ion battery management systems (BMS) remains a critical bottleneck in electric vehicle range predictability, fast-charging safety, and pack longevity. Conventional BMS firmware is polarized between two inadequate paradigms: empiri...

A. Emre Cetin · 0 citations
#edge computing Open access Sep 2026

Deep Permutation Networks: Layerwise Invariant Manifolds, Closed-Form Attractor Splicing, and Zero-Backpropagation Topological Learning

For four decades, deep artificial neural networks have relied on continuous vector spaces, dense floating-point General Matrix Multiplications (GEMM: hl+1 = σ(Wlhl + bl)), and gradient-based backpropagation. While effective in data centers, this paradigm incurs severe thermodynamic, memory bandwidth, and numerical stab...

A. Emre Cetin · 0 citations
#edge computing Open access Sep 2026

Real-Time Aerodynamic Flow Reconstruction from Ultra-Sparse Sensors via Deep Permutation Networks (DPN) and Idempotent Physical Projections

Real-time estimation of full unsteady aerodynamic flow fields $\mathbf{u}(\mathbf{x}, t) = (u, v)$ from ultra-sparse discrete sensor observations (e.g., $M \le 10$ point velocity probes across thousands of grid cells) is a foundational challenge in active flow control, wind tunnel telemetry, and unmanned aerial vehicle...

A. Emre Cetin · 0 citations
#diffusion models Open access Sep 2026

Deterministic Electrochemical Battery State Estimation via Volume-Weighted Lithium Mass Hyperplane Projections: Achieving Zero-Drift SoC and Hard Real-Time BMS on Microcontrollers

Precise on-board estimation of State of Charge (SoC) and State of Health (SoH) in lithium-ion battery management systems (BMS) remains a critical bottleneck in electric vehicle range predictability, fast-charging safety, and pack longevity. Conventional BMS firmware is polarized between two inadequate paradigms: empiri...

A. Emre Cetin · 0 citations
#diffusion models Open access Sep 2026

Deterministic Electrochemical Battery State Estimation via Volume-Weighted Lithium Mass Hyperplane Projections: Achieving Zero-Drift SoC and Hard Real-Time BMS on Microcontrollers

Precise on-board estimation of State of Charge (SoC) and State of Health (SoH) in lithium-ion battery management systems (BMS) remains a critical bottleneck in electric vehicle range predictability, fast-charging safety, and pack longevity. Conventional BMS firmware is polarized between two inadequate paradigms: empiri...

A. Emre Cetin · 0 citations
#edge computing Open access Sep 2026

Real-Time Aerodynamic Flow Reconstruction from Ultra-Sparse Sensors via Deep Permutation Networks (DPN) and Idempotent Physical Projections

Real-time estimation of full unsteady aerodynamic flow fields $\mathbf{u}(\mathbf{x}, t) = (u, v)$ from ultra-sparse discrete sensor observations (e.g., $M \le 10$ point velocity probes across thousands of grid cells) is a foundational challenge in active flow control, wind tunnel telemetry, and unmanned aerial vehicle...

A. Emre Cetin · 0 citations
#edge computing Open access Sep 2026

Real-Time Aerodynamic Flow Reconstruction from Ultra-Sparse Sensors via Deep Permutation Networks (DPN) and Idempotent Physical Projections

Real-time estimation of full unsteady aerodynamic flow fields $\mathbf{u}(\mathbf{x}, t) = (u, v)$ from ultra-sparse discrete sensor observations (e.g., $M \le 10$ point velocity probes across thousands of grid cells) is a foundational challenge in active flow control, wind tunnel telemetry, and unmanned aerial vehicle...

A. Emre Cetin · 0 citations

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