/**
 * Predictive Coding System
 *
 * Inspired by the brain's predictive processing theory:
 * - The brain constantly predicts incoming sensory data
 * - Only "prediction errors" (unexpected changes) are processed fully
 * - If prediction matches reality, minimal processing is needed
 *
 * For AR tracking:
 * - Predict next frame based on motion model
 * - Compare prediction to actual frame
 * - Skip or minimize processing if difference is below threshold
 * - In static scenes, ~90% of frames can be skipped
 */
export class PredictiveCoding {
    /**
     * @param {number} width - Image width
     * @param {number} height - Image height
     * @param {Object} config - Configuration
     */
    constructor(width: number, height: number, config: Object);
    width: number;
    height: number;
    config: Object;
    frameHistory: any[];
    stateHistory: any[];
    motionModel: {
        vx: number;
        vy: number;
        vtheta: number;
        vscale: number;
        confidence: number;
    };
    blockSize: number;
    blocksX: number;
    blocksY: number;
    blockMeans: Float32Array<ArrayBuffer>;
    prevBlockMeans: Float32Array<ArrayBuffer>;
    consecutiveSkips: number;
    maxConsecutiveSkips: number;
    /**
     * Predict whether current frame can be skipped
     *
     * @param {Uint8Array} inputData - Current frame grayscale data
     * @param {Object} trackingState - Current tracking state
     * @returns {Object} Prediction result
     */
    predict(inputData: Uint8Array, trackingState: Object): Object;
    /**
     * Compute change level between current and previous frame
     * Uses block-based comparison for efficiency
     *
     * @param {Uint8Array} inputData - Current frame
     * @returns {number} Change level (0-1)
     */
    getChangeLevel(inputData: Uint8Array): number;
    /**
     * Compute mean intensity for each block
     * @private
     */
    private _computeBlockMeans;
    /**
     * Predict next tracking state based on motion model
     * @private
     */
    private _predictState;
    /**
     * Store frame for future prediction
     *
     * @param {Uint8Array} inputData - Frame data
     * @param {Object} trackingState - Tracking state
     */
    storeFrame(inputData: Uint8Array, trackingState: Object): void;
    /**
     * Update motion model from state history
     * @private
     */
    private _updateMotionModel;
    /**
     * Check if we're in a static scene (good candidate for aggressive skipping)
     * @returns {boolean} True if scene appears static
     */
    isStaticScene(): boolean;
    /**
     * Reset prediction state
     */
    reset(): void;
    /**
     * Update configuration
     */
    configure(config: any): void;
}