Starting Small: Tips for Self Motivation for New Beginnings
Keep Going I cannot stop thinking about this tweet from @VisualizeValue and how incredible it is for self motivation: Keep going. pic.twitter.com/krKSUPRDbN — Visualize Value (@visualizevalue)
Derivative of Sine and Cosine Using Euler’s Formula
Introduction This posts shows how cosine and sine are related through their derivatives using Euler’s formula. I recall being presented with the derivative of sine
Stop Using Too Many Commas to be a Better Writer
Too many commas destroys the flow of a sentence. I know because I use too many commas. Each comma acts as a pause and too many commas makes good writing sound sluggish and boring.
The problem arises because I write as I’m thinking (I almost put a comma here!) and I put a comma when I need to take a thought break in the middle of sentence. However, you don’t want your reader to have a thought break. You want your reader to flow through your thoughts without a break in concentration. Using too many commas is an easy way to hamper otherwise excellent writing.
In writing the two paragraphs above I removed, or stopped myself from writing, 4-5 commas alone!
Oppenheim DSP Lectures YouTube Video Playlist
I recently came across a playlist on YouTube of Alan Oppenheim’s DSP lectures from 1975. Here’s the link to the playlist. Enjoy!
The Brand New Wave Walker DSP eBook!
The DSP eBook is on Amazon! Update! The eBook is #1 New Release in Signal Processing on Amazon! Currently the #1 New Release in Signal
DFT Frequency Resolution Explained
Frequency resolution is defined as the ability to perfectly distinguish one frequency from another. The DFT frequency resolution is improved by increasing the signal length, not increasing the DFT size. The frequency resolution in radians of the DFT is
(1)
where is the length of the input signal.
In this blog I demonstrate graphically and mathematically why and how increasing the signal length improves the frequency resolution, and why simply increasing the DFT size does not.
Trigonometric Identity: sin(x)^2 + cos(x)^2 = 1
In this post I derive a common trigonometric identity sin(x)^2 + cos(x)^2 = 1 using a form of Euler’s formula.
Is the Nyquist Sampling Rate Satisfied? (Homework Problem)
In this blog I answer a question I received about how to apply Nyquist’s sampling rate mathematically and thought it’s worth sharing. One of the difficult parts about getting started in DSP is the concepts are not intuitive which is further compounded by the requirement that the early work must done mathematically, rather than by building or simulating. Take heart if you feel this way, you are not alone! I hope this blog is useful in helping to understand the mathematics of DSP. Please leave a comment below with other questions you have.
Designing FIR Filter Gain
This blog describes how to design the FIR filter gain through normalization and then applying a gain. Applying filter gain may be desirable to setting the proper amplitude level or power level needed for follow on processing based on threshold values or other reference levels.
Filter design methods may create different gains for the resulting filters such as with Remez, using windowed sinc functions or as specially designed pulse shaping filters. Normalizing the magnitude response of an FIR filter makes the gain 1, or 0 dB, at a desired frequency. A gain factor can then be applied by scaling each of the filter weights.
Can the Fourier Transform Magnitude Be Negative?
I came across a question on DSP Stack Exchange the other day: can the Fourier Transform magnitude be negative? This is a great question! The answer is no, and let’s take a look at why.