Davis Logic V2 Module 70: Polynomial Predictive Trajectory Extension Node

Implementation of a deterministic, zero-allocation numerical differentiation engine for real-time kinematic tracking. The module executes a discrete second-order central finite difference calculation to approximate acceleration from sequential position data points using a signed Q16.16 fixed-point format. Authored by Jamie Davis and last updated on 2026-05-30, it is a 3.5 KB text file available under CC BY 4.0.

Use Cases

• Calculate real-time acceleration from position data based on the described finite difference equation.
• Implement kinematic tracking on bare-metal hardware lacking floating-point capabilities based on the fixed-point arithmetic.
• Develop deterministic, single-cycle execution paths for safety-critical systems based on the zero-heap memory model.
• Benchmark numerical differentiation algorithms against a zero-allocation reference implementation.

Strengths

• Designed for absolute single-cycle execution predictability, as stated in the description.
• Operates entirely in a signed Q16.16 fixed-point data format to avoid floating-point hardware.
• File size is precisely 3.5 KB, indicating a compact implementation.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The description is technical but lacks example data or performance benchmarks.

Provenance

Source

Jamie Davis via figshare

Collection Method

Part of the Davis Logic V2 Architecture; method of data gathering is not specified.

Freshness

Last updated 2026-05-30 17:40:58; freshness should be verified.