Resampled

In the context of data analysis and signal processing, 'resampled' describes the process of changing the sampling rate or density of a dataset. This often involves adjusting the number of data points within a given interval, typically aiming to either increase resolution (upsampling) or decrease data volume (downsampling). The core principle is to derive a new, modified version of the original dataset, where each sample represents a different location or point of time. This transformation is commonly implemented using various algorithms and techniques, such as interpolation and decimation, to approximate the data at the new sampling points.

Resampled meaning with examples

• The audio engineer resampled the music track from 44.1 kHz to 48 kHz to match the video's sampling rate, ensuring perfect synchronization. This involved algorithms to interpolate new data points in the audio, preserving the overall quality while aligning it with the video requirements. This ensured a cohesive media experience.
• To analyze long-term trends in stock prices, the financial analyst resampled the daily data to weekly averages. This downsampling technique reduced the dataset's size, smoothed out short-term volatility, and allowed for easier identification of larger, more impactful market movements. The downsampling strategy clarified overall direction.
• Before training the image recognition model, the dataset was resampled to a consistent resolution. Different image sizes would impede the training process so each picture was transformed, usually downsampling larger images and upsampling smaller ones to create uniformity to improve the model's accuracy. This standardization was essential for success.
• The seismologist resampled the earthquake data to a higher frequency to capture finer details of the seismic waves, thus improving the accuracy of analysis of the seismic data. This increased the density of the data, which was important to understanding the geological makeup where the disturbance happened, enabling more detailed analysis.
• In a time series analysis of a sensor's data, the data scientist resampled the raw measurements to a fixed time interval. This included choosing to take all the data points into account or reducing them to a single sample to better allow for proper comparison. The goal was to generate a new format of the data that could then be used for comparison.