Welcome to the CSP Blog!

To help new readers, I’m supplying here links to the posts that have gotten the most attention over the lifetime of the Blog. Omitted from this list are the more esoteric topics as well as most of the posts that comment on the engineering literature.

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You can see a pre-publication version of my latest CSP journal paper, on “tunneling”, here.

Here are some highlights:

### Cyclostationarity and Machine Learning

A challenge for the Machine Learners: carrier-frequency-offset estimation.

Data set for the Machine-Learner CFO challenge.

Review of ML modulation recognition paper by T. O’Shea.

Review of ML modulation recognition paper by M. Kulin.

Can a machine learn the Fourier transform? Part I. Part II.

How humans learned cyclostationary signal processing.

Analysis of the signals in the data sets used by some Machine Learners: O’Shea RML 2016a, O’Shea RML 2016b, O’Shea 2018, and O’Shea 2016c.

Machine learners’ peculiar terminology and disconnect from mathematics.

The Rants page, which has critical take-downs of mostly (but not all) machine-learning papers in the signal-processing and RF-communications domain.

### What is Cyclostationarity?

Higher-order cyclostationarity.

Suggested posts, in order, for CSP beginners.

### Can I Get Help with my CSP Work Through the CSP Blog?

General rules for getting help.

Second-order estimator development guide.

### What is Higher-Order Cyclostationarity and What are Cyclic Cumulants?

Introduction to higher-order cyclostationarity.

Cyclic cumulants and cyclic moments.

Optional conjugations in higher-order parameters.

Symmetries in higher-order parameters.

### How do You Estimate the Parameters of Second-Order Cyclostationarity?

The frequency-smoothing method for spectral correlation estimation, one cycle frequency at a time.

The time-smoothing method for spectral correlation estimation, one cycle frequency at a time.

Exhaustive efficient spectral correlation estimation, all cycle frequencies (SSCA).

Spectral coherence and blind estimation of significant cycle frequencies.

Exhaustive efficient spectral correlation estimation, all cycle frequencies (FAM).

Second-order estimator development guide.

Symmetries in second-order CSP parameters.

### How do You Estimate the Parameters of Higher-Order Cyclostationarity?

Synchronized averaging and the cyclic-moment-to-cyclic-cumulant formula.

### What are Some Applications of Cyclostationarity?

Noise- and interference-tolerant signal presence detection.

Noise- and interference-tolerant time-delay estimation.

Carrier and symbol synchronization.

### What Estimator and Signal Parameters Affect CSP Performance?

Resolution in frequency, time, and cycle frequency.

Excess bandwidth in digital QAM/PSK.

### Cyclostationarity of Modulated RF Waveforms

Digital QAM/PSK with square-root raised-cosine pulses.

A gallery of spectral correlation functions.

A gallery of cyclic autocorrelation functions.

### Some Mathematical Aspects of CSP

Symmetries in second-order CSP parameters.

Symmetries in higher-order temporal CSP parameters.

Signal processing operations and CSP.

Ambiguity and cyclic correlation.

Conjugation configurations in higher-order moments and cumulants.

Stationary-signal models versus cyclostationary-signal models.

Hi Prof. Chad Spooner,

Do you have plans on writing about frequency-shift (FRESH) filters? Are those filters optimal for cyclostationary and almos cyclostationary signals? I am looking for the most recent publications and trying to learn about the state of the art on this topic.

Thanks!

Not yet! I’ve been working on FRESH filtering a bit lately, and I have a post in the works. But I can’t say exactly when it will be ready. You can see some recent work I did with Matt Carrick in My Papers [45-46].