Fluorescent light in the context of "Frequency spectrum"

A cubicle is a partially enclosed office workspace that is separated from neighboring workspaces by partitions that are usually 5–6 feet (1.5–1.8 m) tall. Its purpose is to isolate office workers and managers from the sights and noises of an open workspace so that they may concentrate with fewer distractions. Cubicles are composed of modular elements such as walls, work surfaces, overhead bins, drawers, and shelving, which can be configured depending on the user's needs. Installation is generally performed by trained personnel, although some cubicles allow configuration changes to be performed by users without specific training.

Cubicles in the 2010s and 2020s are usually equipped with a computer, monitor, keyboard and mouse on the work surface. Cubicles typically have a desk phone. Since many offices use overhead fluorescent lights to illuminate the office, cubicles may or may not have lamps or other additional lighting. Other furniture often found in cubicles includes office chairs and filing cabinets.

In signal processing, the power spectrum ${\displaystyle S_{xx}(f)}$ of a continuous time signal ${\displaystyle x(t)}$ describes the distribution of power into frequency components ${\displaystyle f}$ composing that signal. Fourier analysis shows that any physical signal can be decomposed into a distribution of frequencies over a continuous range, where some of the power may be concentrated at discrete frequencies. The statistical average of the energy or power of any type of signal (including noise) as analyzed in terms of its frequency content, is called its spectral density.

When the energy of the signal is concentrated around a finite time interval, especially if its total energy is finite, one may compute the energy spectral density. More commonly used is the power spectral density (PSD, or simply power spectrum), which applies to signals existing over all time, or over a time period large enough (especially in relation to the duration of a measurement) that it could as well have been over an infinite time interval. The PSD then refers to the spectral power distribution that would be found, since the total energy of such a signal over all time would generally be infinite. Summation or integration of the spectral components yields the total power (for a physical process) or variance (in a statistical process), identical to what would be obtained by integrating ${\displaystyle x^{2}(t)}$ over the time domain, as dictated by Parseval's theorem.