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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of sampling...
Bandpass Sampling01:17

Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2. The spectrum...
Upsampling01:22

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
State Space to Transfer Function01:21

State Space to Transfer Function

The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
Sampling Theorem01:15

Sampling Theorem

In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

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Multiplex holography for space-variant processing: a transfer function sampling approach.

R Kasturi, T F Krile, J F Walkup

    Applied Optics
    |March 24, 2010
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a new holographic method using Fourier plane sampling for space-variant systems. This technique offers an alternative approach to holographic representation by multiplexing system transfer functions.

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    Area of Science:

    • Optics and Photonics
    • Holography
    • Information Optics

    Background:

    • Previous methods for holographic representation of space-variant systems involved input plane sampling.
    • Multiplexing system transfer functions is key to holographic system representation.

    Purpose of the Study:

    • To introduce an alternative multiplexing technique for holographic representation of bandlimited space-variant systems.
    • To explore sampling transfer functions in the Fourier plane for hologram generation.

    Main Methods:

    • Developed a novel multiplexing technique by sampling system transfer functions in the Fourier plane.
    • Investigated various methods for generating multiple input function copies for playback.
    • Utilized computer-generated holograms for experimental validation.

    Main Results:

    • Demonstrated the feasibility of the Fourier plane sampling technique for multiplexed hologram generation.
    • Presented experimental results validating the proposed holographic representation method.
    • Evaluated different input function replication strategies for playback.

    Conclusions:

    • The Fourier plane sampling method provides a viable alternative for holographic representation of space-variant systems.
    • Computer-multiplexed holograms can effectively implement this novel technique.
    • Further research can explore optimizations for input function generation and playback.