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Related Concept Videos

Upsampling01:22

Upsampling

232
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...
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Rectangular and Triangular Pulse Function01:19

Rectangular and Triangular Pulse Function

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The unit rectangular pulse function is mathematically represented by a rectangular function centered at the origin with a height of one unit. This function is defined by two parameters: T, which specifies the center location of the pulse along the time axis, and τ, which determines the pulse duration.
For example, consider a rectangular pulse with a 5V amplitude, a 3-second duration, and centered at t=2 seconds. This pulse can be expressed using the rectangular function, written as,
677
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

237
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
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Bandpass Sampling01:17

Bandpass Sampling

176
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....
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NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences01:17

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences

798
A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
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Arbitrary spectro-temporal pulse-shaping algorithm.

Koyo Watanabe, Takashi Inoue

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    Summary
    This summary is machine-generated.

    Researchers developed a new algorithm for precise optical pulse shaping, enabling control over both temporal intensity and spectral phase. This advancement offers efficient generation of complex spectro-temporal waveforms for advanced optical measurements.

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    Area of Science:

    • Optical Physics
    • Quantum Optics
    • Spectroscopy

    Background:

    • Accurate spectro-temporal pulse shaping is crucial for advanced optical measurement applications.
    • Conventional pulse-shaping methods are limited to controlling only temporal intensity, restricting waveform complexity.

    Purpose of the Study:

    • To introduce a novel algorithm for arbitrary spectro-temporal pulse shaping.
    • To enable simultaneous control over both spectral phase and temporal intensity waveforms.

    Main Methods:

    • Integration of the short-time Fourier transform (STFT) into the iterative Fourier transform algorithm (IFTA).
    • Utilizing spectrogram images as targets for spectro-temporal constraints.
    • Numerical demonstration with various spectro-temporal multi-pulse waveforms.

    Main Results:

    • The proposed algorithm successfully generates arbitrary spectro-temporal pulse waveforms.
    • It effectively determines spectral phase modulation patterns for desired pulse shapes.
    • Demonstrated reduction in computational costs for waveform generation.

    Conclusions:

    • The enhanced IFTA algorithm provides a powerful tool for arbitrary spectro-temporal pulse shaping.
    • This method overcomes limitations of conventional techniques by incorporating spectral phase control.
    • Offers a more efficient approach for generating complex optical waveforms in measurement applications.