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Related Concept Videos

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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Bandpass Sampling

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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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Sampling Continuous Time Signal

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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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Upsampling01:22

Upsampling

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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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Aliasing01:18

Aliasing

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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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Cascaded Op Amps

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Operational amplifiers (op-amps) are versatile electronic components that can be interconnected in a cascade - one after another in a linear sequence. This cascading is possible due to their infinite input resistance and zero output resistance, allowing them to maintain their input-output relationships even when connected in series.
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Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
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Wideband SiN pulse interleaver for optically-enabled analog-to-digital conversion: a device-to-system analysis with

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    We developed a silicon nitride pulse interleaver for advanced analog-to-digital converters (ADCs). This photonic integrated circuit improves signal quality, enabling higher bandwidths for faster data conversion.

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    Area of Science:

    • Photonics and Optical Engineering
    • Integrated Optics
    • Signal Processing

    Background:

    • Silicon nitride photonics offers advantages for integrated optical devices.
    • Time-interleaved analog-to-digital converters (ADCs) require precise signal manipulation.
    • Pulse interleavers are crucial for enhancing ADC performance.

    Purpose of the Study:

    • To design and characterize a silicon nitride pulse interleaver for time-interleaved ADCs.
    • To analyze the performance of the pulse interleaver in an ADC system.
    • To investigate digital signal processing (DSP) equalization techniques for performance enhancement.

    Main Methods:

    • Design of coupled resonator optical waveguide filters with tapered waveguides for a 1.44 THz free spectral range.
    • Experimental characterization of the silicon nitride photonic integrated circuit.
    • Development of a comprehensive model for the time-interleaved photonic-assisted ADC.
    • Evaluation of digital signal processing (DSP) equalization techniques.

    Main Results:

    • Demonstration of a silicon nitride pulse interleaver with a large free spectral range.
    • Analysis of signal distortion and noise sources in photonic ADCs.
    • Successful application of DSP equalization to improve signal-to-noise ratio (SNR).
    • Expected effective number of bits (ENOB) of 5 at 75 GHz (150 GS/s) and 4.3 at 100 GHz (200 GS/s).

    Conclusions:

    • The silicon nitride pulse interleaver is a viable component for high-performance ADCs.
    • DSP equalization significantly enhances the SNR of digitized signals.
    • The proposed system enables high-bandwidth, high-speed data conversion with compact photonic integrated circuits.