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1answer
20 views

Pulse shaping and Baseband filtering

I'm slightly confused about baseband pulse shaping. Let's assume I have a complex data vector in an arbitrary complex constellation (QAM for example). I would like to pass this complex vector through ...
2
votes
1answer
93 views

Compute real signal from a discrete analytic signal

I have a 128MHz-wide down converted signal that gets processed in a FPGA via a polyphase filter bank to give 8x16 MHz baseband analytic signals. How do I convert this analytic signal to a real-valued ...
0
votes
1answer
121 views

Is real-time Hilbert envelope feasible?

Is the Hilbert envelope (analytic signal) feasible to be calculated in audio frames/blocks in real-time, when using FFT with windowing. What I'm specifically concerned with is that how does it not ...
2
votes
3answers
1k views

Calculate and interpret the instantaneous frequency

I'm new to the principle of calculating the instantaneous frequency, and came up with a lot of questions on it. You find them all in a bullet-point list at the end of this text. The text might be a ...
0
votes
2answers
181 views

Recover signal from its spectral amplitude and envelope

I am given an amplitude spectrum (no phase) and the envelope of a signal. What I know about the original signal is, that it can be thought of as wavepacket like structure (sinusoids under a bell curve)...
0
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1answer
163 views

Teager-Kaiser Operator vs. Hilbert Transform

Since a couple of months I started working on the extraction (estimation) of signal frequency and amplitude components by means of two different time-frequency approaches, namely the Hilbert transform ...
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0answers
42 views

What is the relationship between signal and its analytical version?

Hilbert transform is used to transfer signal into analytical signal. But why after the transform, the envelop and instant frequency (if the signal is monogenic) can be calculated. What is happened in ...
0
votes
2answers
170 views

The error between the theoretical value and the simulation value of imaginary part of the FFT results

As we know, a complex analytic signal can be obtained through Fourier transformation of a real value function, and the imaginary part can be reconstructed by Hilbert transform of real part. But I have ...
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0answers
222 views

Instantaneous power estimation by discrete hilbert transform - how far does it smooth?

In my research area, instantaneous power in a specific frequency band is commonly estimated by the following procedure: Apply a bandpass filter on the raw signal (e.g. 80-90Hz bandpass). Estimate ...
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0answers
139 views

How to get the quaternionic analytic signal of a image?

The 2D discrete image signal's quaternionic fourier transform can be described as F(u,v), and its 2D analytic signal often be described as: $$ F_q(u,v) = (1 + \mbox{sgn}(u))(1 + \mbox{sgn}(v)) F(u,v) ...
0
votes
2answers
123 views

number of possible component in sinusoidal model

Suppose that we have the following model $y(t) = A_1\sin(\omega_1 t+\phi_1) + A_2\sin(\omega_2 t+\phi_2) + ... + A_p\sin(\omega_p t+\phi_p) + z(t)$ My question is not related to how to determine the ...
0
votes
0answers
137 views

FFT of complex envelope

I have I and Q samples of a time domain signal, sampled at a rate T, both of length L. I create the complex envelope, C = sampleI+j*sampleQ. Then take the FFT of ...
0
votes
2answers
203 views

How to create a band limited signal of sine waves that is nearly uniform distributed

I would like to create a signal that is nearly uniform distributed (as depicted in Figure 1). It must consist of some single sine waves (e. g. 400 Hz, 430 Hz, 500 Hz) or a random band limited signal (...
2
votes
2answers
100 views

Can signal processing be applied successfully to price data from financial markets?

Price/volume data from financial markets are like signals. Can these information be applied to signal processing to generate profits successfully?
1
vote
2answers
275 views

understanding analytic signals

I know that a function $f_a\in \text{L}^2(\mathrm{R})$ is an analytic signal if its Fourier transform is 0 for negative frequencies, i.e. $\hat{f_a}(\omega)=0$ if $\omega<0$. We can characterize ...
2
votes
1answer
112 views

Revert anayltic signal(length(N/2)) to real signal (length(N))

As a beginner in signal processing, i'll try to explain my problem most thoroughly. I'll firstly explain the idea of the transformation the real valued data has undergone. This includes the ideas and ...
2
votes
2answers
323 views

Prevent negative image with BPSK modulation in a complex signal

In a baseband complex signal, I need to generate a BSPK modulated signal at a given frequency. If I generate a CW at this frequency, all is good. However, when I then BPSK modulate the CW, I get a ...
1
vote
1answer
4k views

Envelope of time domain signal // Hilbert transform

to get the envelope of a time domain signal, s(t), I use the absolute of its analytical time domain signal. But there occur the problem that sometimes the envelope is not as desired a true envelope ...
2
votes
1answer
197 views

Spectrum and Spectrogram explanation

I'm reading this material but I don't understand this example: "An example of a 94% overlap transform processing could be demonstrated by a 279 sample frame with 262 samples overlapped from each ...
3
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0answers
662 views

calculate root mean square, ratio of power, constant false alarm, … of a signal

I am new to Digital Signal Processing, and am reading a paper. I don't know how they can extract some features from signal, like root mean square (RMS), Constant False Alarm Rate - CFAR, Mean Value ...
5
votes
1answer
518 views

Hilbert transform: analytic signal

I want to observe how the signal's phase changes over time and I know Hilbert transform can be used here to get the analytic signal, from which I can extract the amplitude and phase. I know that to ...
3
votes
1answer
122 views

signals comparison metrics

Am new to signal processing and was wondering when given two signals, what are the widely used statistical analysis methods to understand the relationship between them?
21
votes
3answers
575 views

How should I pre-process a real valued signal in order to use Kay's estimator?

I have 100,000 samples of a signal $x[n]$ that was sampled at 20kHz. The data is vibration data from a rotating machine, and contains a significant spectral component related to the speed of the ...