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Videos de Conceptos Relacionados

Upsampling01:22

Upsampling

654
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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Continuous -time Fourier Transform01:11

Continuous -time Fourier Transform

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The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
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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.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
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Downsampling01:20

Downsampling

714
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
714
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

773
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

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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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Video espectral compresivo por codificación dinámica espacial-espectral-temporal con ventanas de codificación.

David Morales-Norato, Andrés Jerez, Miguel Marquez

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    Este resumen es generado por máquina.

    Este estudio introduce un nuevo sistema de video espectral de disparo único para la adquisición eficiente de datos. El enfoque innovador captura videos de espectro completo en una sola exposición, superando las limitaciones de los métodos tradicionales de adquisición múltiple.

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    Área de la Ciencia:

    • Óptica y Fotónica.
    • Procesamiento de imágenes Procesamiento de imágenes.
    • La espectroscopia es una técnica de espectroscopia.

    Sus antecedentes:

    • La imagen compresiva instantánea permite una eficiente adquisición de datos de alta dimensión.
    • La captura de video de espectro completo en una sola instantánea es un desafío debido a la adquisición de dimensiones espectrales y temporales separadas.

    Objetivo del estudio:

    • Desarrollar un sistema de video espectral de un solo disparo comprimido dinámico y codificado por colores.
    • Para abordar las limitaciones en la captura de video espectral dentro de una sola exposición.

    Principales métodos:

    • Emplea un enfoque de codificación temporal con ventanas para mejorar la intensidad de píxeles y el rango dinámico.
    • Sincroniza un filtro sintonizable de cristal líquido con un dispositivo de apertura codificado para la codificación de video espectral.
    • Utiliza un método de multiplicador de dirección alterna plug-and-play (PnP-ADMM) para la recuperación de datos.

    Principales resultados:

    • Demuestra una captura y reconstrucción efectivas de vídeo espectral comprimido.
    • Logra una mejor uniformidad de la intensidad de píxeles y un rango dinámico mejorado a través de la codificación temporal de ventanas.
    • Valida la efectividad del sistema a través de simulaciones extensas y pruebas de concepto experimentales.

    Conclusiones:

    • El sistema propuesto captura y reconstruye de manera eficiente los datos de video espectral en cuatro dimensiones en una sola toma.
    • El nuevo esquema de codificación compresiva y el algoritmo PnP-ADMM ofrecen una solución viable para los desafíos de adquisición de video espectral.