Struct NeuromorphicProcessor 

pub struct NeuromorphicProcessor { /* private fields */ }

Neuromorphic processor for general spatial computations

This processor implements event-driven neuromorphic computing paradigms for spatial data processing. It supports memristive crossbar arrays for in-memory computation and temporal coding schemes for efficient information processing.

Features

• Event-driven processing pipeline
• Memristive crossbar arrays for in-memory computation
• Temporal and rate-based coding schemes
• Spike timing dynamics and correlation detection
• Configurable processing parameters

Example

use scirs2_core::ndarray::Array2;
use scirs2_spatial::neuromorphic::algorithms::NeuromorphicProcessor;

let points = Array2::from_shape_vec((3, 2), vec![
    0.0, 0.0, 1.0, 1.0, 2.0, 2.0
]).unwrap();

let mut processor = NeuromorphicProcessor::new()
    .with_memristive_crossbar(true)
    .with_temporal_coding(true)
    .with_crossbar_size(64, 64);

// Encode spatial data as neuromorphic events
let events = processor.encode_spatial_events(&points.view()).unwrap();

// Process events through neuromorphic pipeline
let processed_events = processor.process_events(&events).unwrap();

Implementations

impl NeuromorphicProcessor

pub fn new() -> Self

Create new neuromorphic processor

Returns

A new NeuromorphicProcessor with default configuration

pub fn with_memristive_crossbar(self, enabled: bool) -> Self

Enable memristive crossbar arrays

When enabled, events are processed through a memristive crossbar array that provides in-memory computation capabilities.

Arguments

• enabled - Whether to enable memristive crossbar processing

pub fn with_temporal_coding(self, enabled: bool) -> Self

Enable temporal coding

When enabled, spatial coordinates are encoded using spike timing rather than spike rates.

Arguments

• enabled - Whether to enable temporal coding

pub fn with_crossbar_size(self, rows: usize, cols: usize) -> Self

Configure crossbar size

Sets the dimensions of the memristive crossbar array used for in-memory computation.

Arguments

• rows - Number of rows in crossbar array
• cols - Number of columns in crossbar array

pub fn with_processing_params( self, max_pipeline_length: usize, crossbar_threshold: f64, learning_rate: f64, ) -> Self

Configure processing parameters

Arguments

• max_pipeline_length - Maximum length of event pipeline
• crossbar_threshold - Threshold for crossbar spike generation
• learning_rate - Learning rate for memristive adaptation

pub fn encode_spatial_events( &self, points: &ArrayView2<'_, f64>, ) -> SpatialResult<Vec<SpikeEvent>>

Encode spatial data as neuromorphic events

Converts spatial data points into spike events using either temporal coding (spike timing) or rate coding (spike frequency) depending on the processor configuration.

Arguments

• points - Input spatial points (n_points × n_dims)

Returns

Vector of spike events representing the spatial data

pub fn process_events( &mut self, events: &[SpikeEvent], ) -> SpatialResult<Vec<SpikeEvent>>

Process events through neuromorphic pipeline

Processes spike events through the neuromorphic computing pipeline, applying memristive crossbar processing and temporal dynamics as configured.

Arguments

• events - Input spike events to process

Returns

Vector of processed spike events

pub fn get_crossbar_statistics(&self) -> HashMap<String, f64>

Get crossbar statistics

Returns statistics about the current state of the memristive crossbar array and event processing pipeline.

Returns

HashMap containing various statistics about the processor state

pub fn crossbar_size(&self) -> (usize, usize)

Get crossbar size

pub fn is_memristive_enabled(&self) -> bool

Check if memristive crossbar is enabled

pub fn is_temporal_coding_enabled(&self) -> bool

Check if temporal coding is enabled

pub fn crossbar_threshold(&self) -> f64

Get current crossbar threshold

pub fn learning_rate(&self) -> f64

Get memristive learning rate

pub fn pipeline_length(&self) -> usize

Get number of events in pipeline

pub fn clear_pipeline(&mut self)

Clear event pipeline

pub fn reset_crossbar(&mut self)

Reset crossbar to initial state

pub fn conductance_matrix(&self) -> &Array2<f64>

Get conductance matrix (for analysis)

pub fn set_conductance( &mut self, row: usize, col: usize, value: f64, ) -> SpatialResult<()>

Set specific conductance value

pub fn get_conductance(&self, row: usize, col: usize) -> Option<f64>

Get specific conductance value

Trait Implementations

impl Clone for NeuromorphicProcessor

fn clone(&self) -> NeuromorphicProcessor

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for NeuromorphicProcessor

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for NeuromorphicProcessor

fn default() -> Self

Returns the “default value” for a type.