What if memory wasn't fixed in neural networks or static matrices β but emerged from a recursive, chaotic shape?
Welcome to the Leonov sequence, a novel numerical recurrence that generates structured chaos with memory and serves as the core of wave-memory.
π The Formula
The sequence is defined recursively:
L_n = |a_n Β· L_{n-1} + b_n Β· L_{n-2} + c_n Β· L_{n-d_n} / (1 + n)|
Where:
- 
a_n, b_n, c_nare random coefficients in range[-2, 2]
- 
d_nis a random delay (1 to 10)
- 
L_0 = 1,L_1 = 1
- The |Β·|ensures non-negative dynamics
This formula creates a dynamic, nonlinear, chaotic sequence with built-in decaying memory β unlike traditional sequences such as Fibonacci.
π Why Is It Interesting?
| Property | Leonov Sequence | Fibonacci | Logistic Map | Random Walk | 
|---|---|---|---|---|
| Memory | β Yes (d_n lag) | β No | β No | β No | 
| Chaos | β Tunable | β None | β Full chaos | β Noise | 
| Entropy | π‘ Moderate | π΅ Low | π΄ High | π΄ High | 
| Autocorrelation | β Present | β High | β None | β Random | 
| Application | π§ Geometry, cognition | Math demo | Population models | Noise models | 
π¦ Example in Rust
use wave_memory::{GeoForm, Wave};
fn main() {
    // Create a geometric form using the Leonov sequence
    let mut form = GeoForm::from_leonov(64, 123);
    // Initialize a wave with an impulse at the center
    let mut wave = Wave::new(64, 32);
    // Run the wave and let the form adapt to its energy
    for _ in 0..50 {
        wave.step(&form);
        let energy = wave.energy();
        form.adapt(&energy, 0.1);
    }
    // Inspect a value from the adapted form
    println!("Form at center: {:.4}", form.data[32]);
}
π§ Applications
- π Wave-based memory: used in wave-memory
- π§± Fractal form generation
- π¬ Cognitive geometry
- π Emergent computation
This sequence is not just a generator β itβs a primitive architecture of form that adapts.
 

 
    
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