Researchers have proposed a novel framework for token stream analysis, utilizing dual-level exponential rolling average centroids (ERACs). This sophisticated approach enables pattern detection and guides point movement by tracking multiple ERACs at both global and type-specific levels. The system processes tokens independently and in parallel, allowing for the formation of complex patterns.
The framework's primary mechanism is a signal propagation flow that defines two distinct categories of tokens: primitive and higher-order tokens. Each token instance generates points that participate in pattern detection and signal propagation. The dual-level ERAC system continuously updates global and type-specific centroids, preventing unwanted point clustering and enabling real-time pattern formation.
This framework has the potential to revolutionize the field of token stream analysis, allowing for more advanced experimental approaches and scientific-like exploration. The ability to trigger and suppress specific token instances enables a foundation for controlled experimentation and outcome analysis.