The phrase "a sequence of segments" is correct and usable in written English.
It can be used in contexts where you are describing a series of connected parts or elements, often in fields like mathematics, computer science, or literature.
Example: "The data is organized into a sequence of segments, each representing a different phase of the project."
Alternatives: "a series of segments" or "a chain of segments".
Compound pipes are assembled as a sequence of segments, each of which has a constant curvature.
The approach also allows us to break the production model into a sequence of segments.
First, video files are represented by a sequence of segments each of which contains colour histograms, starting time, and a set of phonemes.
Given a starting point in such a domain, the resulting steepest descent path is represented by a sequence of segments terminating at a local minimum.
A buffered digital differential analyzer (BDDA) algorithm in a computerized numerical controller (CNC) performs milling electric discharge machining (milling EDM'ing) of a curve constructed from a sequence of segments using a traditional computer-aided manufacturing (CAM) system.
In general, a JPEG file consists of a sequence of segments, each beginning with a marker (2 bytes).
Assuming that an audio signal has been divided into a sequence of audio segments using fixed window segmentation, our works focus on categorizing these audio segments into a set of predefined audio classes.
c i t + 1 = ∑ j = max 0, i − n 0 min k, t ⋅ n 0 c i t and c i 1 = 1 i = 0, 1, …, n 0. Since a route consists of a sequence of road segments, the route probability of connectivity is the product of it for all segments along the route.
Although any sufficiently smooth curve can be fitted with any specified precision by a sequence of parabolic segments, our observations have shown that monkey drawing movements are composed of a small number of relatively long parabolic segments.
Popular trajectory optimization software, such as TrajOpt, represents the trajectory as a sequence of linear segments between waypoints.
The methodology firstly characterizes the wave height time series by approximating it using a sequence of labeled segments, and then a binary classifier is trained to predict the occurrence of SSWH periods based on past height values.
