Signal Tagging via Adaptive Windowing in Time-Variant Data

The patent applies dynamics by making the smoothing window adaptive rather than fixed. The window dynamically adjusts its boundaries based on detected signal transitions and interruptions. When a signal interruption is detected, the window resets or adjusts to exclude the interruption period, maintaining smoothing accuracy without being disrupted by temporary signal gaps. This dynamic adaptation allows the system to maintain reliability during interruptions while preserving measurement precision.

The patent changes the parameter of the smoothing window from a fixed time-based approach to a signal-state-based approach. By monitoring signal characteristics and adjusting the window parameters (start and end points) based on detected signal presence and transitions, the system adapts the smoothing process to current signal conditions. This parameter change enables the system to handle interruptions and multiple signals effectively while maintaining accurate signal identification.

The patent applies preliminary action by performing signal classification and identifying potential signals of interest in a first pass through the data. During this initial scan, the system pre-identifies candidate signals and their time ranges, then uses this preliminary information to guide the second pass where actual smoothing and identification occur. This preliminary classification reduces the computational burden of the second pass and eliminates the need for multiple additional passes, thereby maintaining high accuracy while reducing total processing time.

The patent segments the signal processing task into distinct phases: a first pass for classification and candidate identification, and a second pass for detailed smoothing and signal confirmation. By dividing the processing into these segments with different objectives, the system achieves accurate signal identification in the second pass while the first pass prepares the data structure to minimize the need for further re-processing, thus reducing overall processing time compared to traditional multiple-pass approaches.

The patent transforms the fixed time window into a dynamic window that automatically adjusts its boundaries based on signal conditions. The window starts at detected signal transitions and ends at subsequent transitions or interruptions, making it adaptable to variable signal lengths and gaps. This dynamic approach maintains relative implementation simplicity while dramatically improving adaptability to different signal conditions, interruptions, and multiple concurrent signals.

The smoothing system performs self-service by automatically detecting signal transitions and using them to define the smoothing window boundaries without requiring external configuration or manual adjustment. The system monitors its own input signal, identifies transitions autonomously, and adjusts the window parameters accordingly. This self-adjusting capability provides high adaptability to varying signal conditions while keeping the implementation relatively simple, as the system configures itself based on observed signal characteristics.