Vertical Slice Architecture solution template in .NET 9
Torchhd is a Python library for Hyperdimensional Computing and Vector Symbolic Architectures
Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed), with high stress seen as an indication of deception. In this work, we propose a deep learning-based psychological stress detection model using speech signals. With increasing demands for communication betwee…
Rohde & Schwarz SCPI Driver (in Python)
Holographic Reduced Representations
Domain-Agnostic Supervised Learning with Hyperdimensional Computing
Thesis project on the development of a framework for Value-Set Analysis
Video streaming web application [VSA], through HLS, using AES-128 encryption
a basic VSA sample in c#
A modern .NET 9 Web API starter template using Vertical Slice Architecture and REPR+V pattern.
Volume Spread Analysis (VSA) is a powerful trading methodology that examines the relationship between volume, price spread (range), and closing price to identify market reversals, continuations, and potential manipulation by "smart money."
"VSA, Analogy, and Dynamic Similarity" presentation given at the Workshop on Developments in Hyperdimensional Computing and Vector Symbolic Architectures, Heidelberg, Germany, 2020-03-16.
Publications by Peter Overmann
An extended note on using Vector Symbolic Architectures to implement Next Generation Reservoir Computing
[code] Behavioral Time Scale Synaptic Plasticity (BTSP) endows Hyperdimensional Computing with brain-like information retrieval flexibility
This project aims to develop a very basic Vector Symbolic Architecture model to use as a default model in my other VSA projects.
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