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Results tagged with self-study
Search options not deleted
user 5119
This tag means the asker is new to the DSP field and is requesting extra guidance. It has similar connotations to the homework tag, but this lets potential answerers know they should probably do more than guide the self-studier compared with the homework requester.
0
votes
1
answer
257
views
Beginner level confusion regarding symbols used in modulation
For 4-QAM symbol sequence, each symbol can be represented by $k=\log_2(4) = 2$ bits. 4-QAM constellation can be generated using s = round(rand(1,T)*2 -1)
For 16-QAM, the symbol sequence takes 4 ampli …
- 616
0
votes
1
answer
332
views
Constant modulus algorithm - performance poor?
The question is based on a research article titled, "Novel Robust Blind Equalizer for QAM Signals
Using Iterative Weighted-Least-Mean-Square
Algorithm"
The Authors have proposed an equalization schem …
- 616
4
votes
1
answer
4k
views
Design of equalizer for wireless communication
I am having difficulty in trying to understand the working mechanism of an equalizer. Please correct me where wrong.
Mechanism of an Equalizer - The purpose of an equalizer is to reduce intersymbol …
- 616
0
votes
1
answer
78
views
Is there a rule of thumb for selecting the variance of the input?
Considering an estimation problem, where I want to estimate the unknown input $x$ using the known channel parameters. This estimation problem can be solved by Least Squares.
Thus, the model is $$\hat …
- 616
0
votes
1
answer
104
views
Error plot between known and estimated data
The channel is an FIR model with input $u$. The input takes in values which are symbols from some constellation. Using an equalizer such as the Least Mean Squares (LMS), I estimate the input to the ch …
- 616
1
vote
1
answer
229
views
Performance of adaptive filters
Can somebody please provide an intuitive answer or reference for the following questions?
Q1: Dependence of estimation performance on number of data points -- I could not find any information whether …
- 616
2
votes
1
answer
149
views
How to represent the nonlinear model as a state space in Unscented Kalman Filter
There is an Autoregressive model of order 1 (AR(1)) that is excited by a non-linear signal as the input:
$$x_t = \rho x_{t-1} + u_t \tag{1}$$
The time series $u_t$ is generated from a nonlinear map,
$ …
- 616
0
votes
1
answer
591
views
Proper method for generating Channel coefficients in MATLAB
I am trying to estimate the coefficients of a Moving average model using popular estimation method such as Least Squares (LS). For educational purposes, I am trying to see if LS can work well when the …
- 616
1
vote
0
answers
324
views
What is the difference between entropy and entropy rate and which one is important in inform... [duplicate]
By entropy I understand the uncertainty or randomness. But if the uncertainty is high then what is its implication and advantage in transmitting information or as an information source or is high entr …
- 616
3
votes
2
answers
153
views
Why use parametric based estimation methods - confusion regarding terms
Using the probability density function (pdf) we can estimate an unknown parameter using methods such as Maximum Likelihood estimation. If the pdf is not available, then Least Squares can be used. Oth …
- 616
1
vote
1
answer
1k
views
Unable to understand the derivation of the update equation for LMS
I am trying to follow the derivation of the Least Mean Square https://en.wikipedia.org/wiki/Least_mean_squares_filter#Proof
but I cannot get the update rule. I am stuck in the following steps and sha …
- 616
2
votes
1
answer
710
views
Concepts: Ideal and Non Ideal Channel Resulting in Inter Symbol Interference
I am following the book: Blind equalization and Identification by Zhi Ding and Ye Li. In Chapter 2, the concept of T spaced equalizers is presented. It is mentioned that the output of the channel is $ …
- 616
1
vote
1
answer
256
views
Doubts and some confusion on variance for complex rv
This question is in continuation of the one asked here.
Let's say that the measurement noise $w$ or any random variable is circularly Gaussian complex.
If the imaginary and real components each ha …
- 616
1
vote
1
answer
140
views
Notations to Use in Formulating of Maximum Likelihood Estimation
The received
noisy signal $y_n \in \mathbb{R}$ is expressed as:
\begin{align}
y_n = \mathbf{h}^\mathsf{T}\mathbf{u}_n + w_n.
\tag{1}
\end{align}
$\mathbf{h} = [h_0,h_1,\ldots,h_{p-1}]^\mathsf{T} \in …
- 616
4
votes
1
answer
268
views
Relationship between information retrieval and source separation in signal processing
In machine learning, for the task of classifying input data (called an example) which are in binary representation, $\mathbf{x}\in \mathbb{R}^D$, $\mathbf{x} \in \{0,1\}^D$ into its multiple class lab …
- 616