Exponential Moving Average (EMA) is a statistical technique used to analyze time-series data by smoothing out short-term fluctuations. It assigns exponentially decreasing weights to past observations, giving more importance to recent data points while still retaining information from older ones. This method effectively reduces noise in inputs, making trends more discernible in datasets such as financial markets or sensor readings.
