Signal Distortion
Signal Distortion - Related Videos
01:02
¹H NMR: Interpreting Distorted and Overlapping Signals
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2024
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum. As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are slanted or...
13:44
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Cited by 13 •
2013
We demonstrate methods for the detection of architectural distortion in prior mammograms. Oriented structures are analyzed using Gabor filters and phase portraits to detect sites of radiating tissue patterns. Each site is characterized and classified using measures to represent spiculating patterns. The methods should assist in the detection of breast cancer.
07:03
Medical-grade Sterilizable Target for Fluid-immersed Fetoscope Optical Distortion Calibration
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Cited by 6 •
2017
This article describes the design and development of a sterilizable custom camera optical distortion calibration target for the peri-operative, fluid-immersed calibration of endoscopes during endoscopic interventions.
06:51
Measuring the Complete-arch Distortion of an Optical Dental Impression
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Cited by 4 •
2019
Here, we present a protocol to measure the degree of distortion at each part of the compete-arch digital impression acquired from an intraoral scanner with 3D-printed metal phantom with standard geometries.
01:26
Signal and System
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2024
A signal x(t) is a set of data or a time function representing a variable of interest. Signals typically convey information about a phenomenon, such as atmospheric temperature, humidity, human voice, television images, a dog's bark, or birdsongs. More generally, a signal can be a function of more than one independent variable. For instance, images depend on horizontal and vertical positions and can be regarded as two-dimensional signals. However, this text will focus on one-dimensional signals...
FAQs
Matrix components can alter analytical response when they absorb or scatter radiation, changing apparent intensity and baseline. In spectroscopy, this can make analyte response differ from the underlying amount even when analyte composition is unchanged. Recognizing matrix-related effects guides blank correction and sample preparation, helping separate sample-background contributions from chemically meaningful signal.
Overlapping analyte signals can combine in spectra or chromatograms, making individual components difficult to distinguish. The resulting signal may resemble a single feature or change its apparent intensity, which can impair analyte identification and quantitative accuracy. Recognizing overlap as a possible source of distortion helps researchers avoid interpreting combined responses as evidence for only one chemical component.
A detector near saturation may no longer produce a proportional response to increasing analyte signal. This nonlinearity can change measured intensity and compromise quantitative comparisons, even when the sample composition is unchanged. Appropriate measurement conditions and calibration are therefore important for identifying departures from linear response and preventing detector behavior from being mistaken for chemical variation.
Researchers can compare analytical responses with blanks, apply calibration, and use sample preparation to reduce background contributions from the matrix. They can also select measurement conditions that avoid detector saturation and make overlapping features easier to evaluate. Together, these steps help distinguish instrumental artifacts from genuine composition changes and improve the accuracy and reproducibility of quantitative results.
Its observable form depends on the analytical platform and the source of interference. Spectroscopy may show altered intensity or baseline behavior, while chromatography may show overlapping or broadened peaks. Electrochemical measurements and sensor development also require attention to response reliability. Across these areas, the central task is separating measurement artifacts from information about chemical composition.
Controlling distortion strengthens several outcomes that analytical chemistry relies on, including analyte identification, detection limits, quantitative accuracy, and reproducibility. These benefits matter in spectroscopy, chromatography, electrochemistry, and sensor development because misleading intensity, peak shape, position, or timing can obscure chemical information. Better control supports more dependable interpretation of measured responses and comparisons among samples.