摘要:
Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed. The reconstructed signal (x(t)) can be represented as a sequence of known functions (γ(t)) weighted by the weigths (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (ρ) of the first signal (x(t)).
摘要翻译:一种用于重新构造以次奈奎斯特速率规则采样的第一信号(x(t))的重构方法,包括从规则间隔的采样值(y N s [n],y(n T ))一组权重(c N,N,C,N,C,C),并且移位(t N n, 可以重构所述第一信号(x(t))。 重构信号(x(t))可以表示为由重量(c)k N加权并且移位了移位(t≠k)的已知函数(gamma(t))的序列 SUB>)。 采样率至少等于第一个信号(x(t))的创新速率(rho)。
摘要:
Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed. The reconstructed signal (x(t)) can be represented as a sequence of known functions (γ(t)) weighted by the weights (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (ρ) of the first signal (x(t)).
摘要:
Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed.The reconstructed signal (x(t)) can be represented as a sequence of known functions (γ(t)) weighted by the weights (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (ρ) of the first signal (x(t)).
摘要:
Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed.The reconstructed signal (x(t)) can be represented as a sequence of known functions (γ(t)) weighted by the weigths (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (ρ) of the first signal (x(t)).
摘要:
Reconstruction method for reconstructing a first signal (x(t)) regularly sampled at a sub-Nyquist rate, comprising the step of retrieving from the regularly spaced sampled values (ys[n], y(nT)) a set of weights (cn, cnr, ck) and shifts (tn, tk) with which said first signal (x(t)) can be reconstructed.The reconstructed signal (x(t)) can be represented as a sequence of known functions (γ(t)) weighted by the weights (ck) and shifted by the shifts (tk). The sampling rate is at least equal to the rate of innovation (ρ) of the first signal (x(t)).
摘要:
A reconstruction method for reconstructing a first signal from a set of sampled values generated by sampling a second signal at a sub-Nyquist rate and at uniform intervals, the method includes retrieving from the set of sampled values a set of shifts and weights with which the first signal can be reconstructed.
摘要:
The present invention relates to a method of processing a signal which is received by a receiver, comprising, obtaining an analog signal (yt) based on another signal (xt) and noise; defining a sampling kernel based on the noise; and using the sampling kernel to obtain at least one sample (yn) from the analog signal (yt). The invention also relates to a corresponding apparatus; computer program product; headset; watch, and sensing device.
摘要:
Signals, including signals from outside of the subspace of bandlimited signals associated with the Shannon theorem, are acquired while still providing an acceptable reconstruction. In some aspects a denoising process is used in conjunction with sparse sampling techniques. For example, a denoising process utilizing a Cadzow algorithm may be used to reduce the amount of noise associated with sampled information. In some aspects the denoising process may be iterative such that the denoising process is repeated until the samples are denoised to a sufficient degree. In some aspects, the denoising process converts a set of received samples into another set corresponding to a signal with a Finite Rate of Innovation (FRI), or to an approximation of such a signal. The disclosure relates in some aspects to combination of a denoising process with annihilating filter methods to retrieve information from a noisy, sparse sampled signal. The disclosure relates in some aspects to determining a sampling kernel to be used to sample the signal based on noise associated with the signal. The disclosure relates in some aspects to determining the number of samples to obtain from a signal over a period of time based on noise associated with the signal. The disclosure relates in some aspects to determining the finite number of innovations of a received signal.
摘要:
A method of signal processing, comprising: obtaining a digital signal (yn) based on another signal (xt) and noise; and estimating information relating to the another signal (xt) by using a denoising process to produce a denoised signal (y′n) and by processing the denoised signal (y′n), wherein the denoised signal (y′n) produced by the denoising process has a substantially Finite Rate of Innovation.
摘要:
Signals, including signals from outside of the subspace of bandlimited signals associated with the Shannon theorem, are acquired while still providing an acceptable reconstruction. In some aspects a denoising process is used in conjunction with sparse sampling techniques. For example, a denoising process utilizing a Cadzow algorithm may be used to reduce the amount of noise associated with sampled information. In some aspects the denoising process may be iterative such that the denoising process is repeated until the samples are denoised to a sufficient degree. In some aspects, the denoising process converts a set of received samples into another set corresponding to a signal with a Finite Rate of Innovation (FRI), or to an approximation of such a signal. The disclosure relates in some aspects to combination of a denoising process with annihilating filter methods to retrieve information from a noisy, sparse sampled signal. The disclosure relates in some aspects to determining a sampling kernel to be used to sample the signal based on noise associated with the signal. The disclosure relates in some aspects to determining the number of samples to obtain from a signal over a period of time based on noise associated with the signal. The disclosure relates in some aspects to determining the finite number of innovations of a received signal.