amHistogramm

amHistogramm is a term used to describe a histogram that visualizes the distribution of amplitude values in a signal or dataset. It is commonly employed in audio processing, communications, and sensor data analysis to summarize how often different amplitude levels occur.

A typical amHistogramm represents amplitude on a finite set of bins. The range of amplitudes is divided into evenly spaced intervals, and each bin records the number of samples whose amplitude falls within that interval. The histogram can be shown in linear or logarithmic (often dB) scale to accommodate wide dynamic ranges. Normalization is common, yielding a probability distribution where the bin values sum to one, or a cumulative histogram that reflects the accumulating probability up to each bin.

Construction and interpretation: to build an amHistogramm, one selects the number of bins, establishes the minimum and maximum amplitude values, and counts samples per bin. The result highlights characteristics such as central tendency, skewness, and the presence of outliers or clipping. A uniform histogram suggests a broad, even distribution of amplitudes, while a skewed histogram indicates dominance of low or high amplitudes.

Variants and extensions: amHistograms can be computed over sliding time windows to track changes over time, produced separately for multiple channels, or combined into a multi-dimensional histogram. Smoothed versions or kernel density estimates may substitute for discrete bin counts to provide a continuous view of the distribution.

Relation to related concepts: amHistogramm is related to standard histograms, probability distributions, and cumulative distribution functions. It often serves as a diagnostic tool for loudness, dynamic range, noise floor estimation, and signal normalization.