# Tag Info

Accepted

### FIR Filter Design: Window vs Parks McClellan and Least Squares

I agree that the windowing filter design method is not one of the most important design methods anymore, and it might indeed be the case that it is overrepresented in traditional textbooks, probably ...
• 90.3k
Accepted

### High Dynamic Range FIR Filters

Like @MattL. and @aconcernedcitizen say, the issue is numerical. Python's scipy.signal.firls uses internally the solver ...
• 13.5k
Accepted

• 19.7k
Accepted

### FIR filter design with nonlinear phase from measured amplitude and phase responses

The algorithm gives you the best least squares approximation possible for a causal filter with the specified filter order and the given desired frequency response. The problem with your specification ...
• 90.3k
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• 1,430
Accepted

• 90.3k

### Solving LASSO (${L}_{1}$ Regularized Least Squares) with Gradient Descent

It can easily solved by the Gradient Descent Framework with one adjustment in order to take care of the ${L}_{1}$ norm term. Since the ${L}_{1}$ norm isn't smooth you need to use the concept of ...
• 19.7k
Accepted

### What Is the Definition of Linear Predictive Coefficients When the Optimal Value Aren't Unique?

Constant zero sequence is the only finite sequence for which $a_i$ are not uniquely defined. Indeed, $a_i$ are a solution to the equation  \begin{bmatrix} R_0 && R_1 && \ldots &...
• 151
Accepted

### Design of FIR Filters with Arbitrary Magnitude and Phase Responses

For the sake of clarity, let me point out that you do not approximate $(1)$ by $(2)$, but the other way around: you approximate a desired frequency response, i.e., your specification, by the filter's ...
• 90.3k