Windowing

Windowing is a technique used in signal processing and data analysis to segment a large dataset into smaller, more manageable pieces called windows. Each window contains a subset of the original data and can be analyzed independently. Windowing is commonly used in time series analysis, where a signal is sampled over time and analyzed for patterns or trends. By dividing the signal into windows, it is possible to identify changes in the signal over time and to analyze the signal in more detail. Windowing can also be used in image processing, where an image is divided into smaller sections for analysis. In this case, the windows are typically rectangular or square regions of the image. Windowing can be performed using a variety of techniques, including rectangular, triangular, and Hamming windows.