sinc filter造句

• :We do have an article specifically on the sinc filter.
• The sinc filter is not bounded-input bounded-output ( BIBO ) stable.
• The Lanczos filter is one of many practical ( finitely supported ) approximations of the sinc filter.
• :A sinc filter is a lowpass filter ( with a really, really sharp cutoff ).
• This occurs for instance in using the sinc filter as an ideal ( brick-wall ) low-pass filter.
• Could someone please explain to me the concepts behind a Sinc Filter especally how they relate to Anti-Aliasing and the function sin ( x ) / ( x ).
• A general solution is to use a window function on the sinc filter, which cuts off or reduces the negative lobes : these respectively eliminate and reduce overshoot and ringing.
• In signal processing, the oscillations of the sine integral cause overshoot and ringing artifacts when using the sinc filter, and frequency domain ringing if using a truncated sinc filter as a low-pass filter.
• In signal processing, the oscillations of the sine integral cause overshoot and ringing artifacts when using the sinc filter, and frequency domain ringing if using a truncated sinc filter as a low-pass filter.
• In signal processing, a "'sinc filter "'is an idealized filter that removes all frequency components above a given cutoff frequency, without affecting lower frequencies, and has linear phase response.
• Real-time filters can only approximate this ideal, since an ideal sinc filter ( a . k . a . " rectangular filter " ) is sampling theorem and the Whittaker Shannon interpolation formula.
• However, in the sinc filter, the lobes monotonically decrease in magnitude and alternate in sign, as in the alternating harmonic series, and thus tail integrals alternate in sign as well, so it exhibits overshoot as well as ringing.
• As the sinc filter has infinite impulse response in both positive and negative time directions, it must be approximated for real-world ( non-abstract ) applications; a kernel in order to use it on any practical real world data set reduces its ideal properties.
• The high-pass filter with lower band edge " B " " H " is just a transparent filter minus a sinc filter, which makes it clear that the Dirac delta function is the limit of a narrow-in-time sinc filter:
• The high-pass filter with lower band edge " B " " H " is just a transparent filter minus a sinc filter, which makes it clear that the Dirac delta function is the limit of a narrow-in-time sinc filter:
• When the baseband filters in the communication system satisfy the Nyquist criterion, symbols can be transmitted over a channel with flat response within a limited frequency band, without ISI . Examples of such baseband filters are the raised-cosine filter, or the sinc filter as the ideal case.
• In the case of windowed sinc filters, the frequency response of the reconstruction filter can be understood in terms of the frequency response of the window, as the frequency response of a windowed filter is the convolution of the original response ( for sinc, a brick-wall ) with the frequency response of the window.
• Notably, the frequency response of the rectangular filter is the sinc function ( the rectangular function and the sinc function are Fourier dual to each other ), and thus truncation of a filter in the time domain corresponds to multiplication by the rectangular filter, thus convolution by the sinc filter in the frequency domain, causing ripple.
• A key source of ripple in digital signal processing is the use of window functions : if one takes an infinite impulse response ( IIR ) filter, such as the sinc filter, and windows it to make it have finite impulse response, as in the window design method, then the frequency response of the resulting filter is the convolution of the frequency response of the IIR filter with the frequency response of the window function.