Lessons from Optics, the Other Deep Learning

Re:Lessons from Optics, the Other Deep Learning by wrycoder on Monday February 12, 2018 @03:13PM (#16361634)

A couple of times, I've heard Gerry Sussman at MIT (SICP author) give a talk on how bipolar transistor circuits are actually designed. You don't use SPICE or mesh analysis except in unusual circumstances (e.g. non-linear circuits) or to fine tune a completed design.

As an example, a bias design goes something like this: "Let's see, I'll pin the base at five volts with a resistor divider. The emitter will be 0.6V below that. Then the emitter current will be (5.0 - 0.6) divided by the emitter resistor. The collector current will be essentially the same, so I can pick the collector load resistor to give me an appropriate quiescent point and make sure the output impedance is less than a tenth of the input impedance of the following stage (so I can ignore the latter)."

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Re:Lessons from Optics, the Other Deep Learning by analog31 on Monday February 12, 2018 @08:05PM (#16363915)

The classic Art of Electronics by Horowitz and Hill definitely taught this approach. It's considered to be a hard textbook for undergraduates, but is also a joy to read and study for pleasure.

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Re:Lessons from Optics, the Other Deep Learning by vvanders on Monday February 12, 2018 @10:49PM (#16364592)

Can't upvote enough, that book is a treasure. Expensive but totally worth it.

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Re:Lessons from Optics, the Other Deep Learning by amelius on Tuesday February 13, 2018 @02:46PM (#16370090)

Sorry, but I can't agree. It's basically a cookbook. It doesn't present the material in an analytical style.

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Re:Lessons from Optics, the Other Deep Learning by vvanders on Tuesday February 13, 2018 @04:53PM (#16371166)

Is that a bad thing? For me the value wasn't in the cookbook aspect but in the explanation of the practical considerations when it comes to engineering a design.

Knowing a parameter in detail isn't nearly as important as knowing if that parameter matters in the scope of the final design.

The book is also pretty honest about that and goes to pretty good lengths to guide readers to deeper material if it's an area they want to understand in greater depth.

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Re:Lessons from Optics, the Other Deep Learning by ehead on Tuesday February 13, 2018 @09:43AM (#16367442)

Seconded. This book should be given to all EE undergraduates, it’s a shame how few people know about it.

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Re:Lessons from Optics, the Other Deep Learning by vvanders on Tuesday February 13, 2018 @12:12PM (#16368751)

Yup, I've lent/given away my various copies over the years many times.

A true testament that even in there modern days the principals taught are still solid.

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Re:Lessons from Optics, the Other Deep Learning by taeric on Monday February 12, 2018 @03:18PM (#16361672)

https://www.infoq.com/presentations/We-Really-Dont-Know-How-... is the version of the talk I've seen. Highly recommended to everyone.

I have yet to get his classical mechanics book. Gonna have to pull the trigger on that soon.

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Re:Lessons from Optics, the Other Deep Learning by wrycoder on Monday February 12, 2018 @10:05PM (#16364426)

I haven't had a chance to ask him why he didn't cover special relativity. Seemed like a great fit for a computation-based course.

Edit: Thanks for that - it's more detailed than the talks I attended (LibrePlanet).

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Re:Lessons from Optics, the Other Deep Learning by awful on Tuesday February 13, 2018 @09:14AM (#16367222)

We were taught to do it that way, without having access to spice and computers in general, using the data sheets and maybe a curve tracer if you were lucky.

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