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From: Le Chaud Lapin on 9 Jul 2010 01:40 On Jul 8, 2:55 pm, "Nasser M. Abbasi" <n... (a)12000.org> wrote:> 1. DSP courses Has the most math. (including complex variables). > 2. Two domains to worry about, time and frequency. Jumping from one to > the other can get confusing. > 3. Two other domains to worry about, continuous time vs. discrete time. > 4. Many relations between many concepts to get right. > 5. One has to also be good in programming. > 6. Demodulation is just hard. Filter design is hard. > 7. Need to also be good in probability and statistics to do random > signals (real life). > 8. Has to know how to do lab work also. Hard stuff. DSP, rather, signal processing in general, was hard for me, not because of the math or the concepts, but because I felt my foundation was not strong. In particular, Fourier theory drove me crazy. I remember a post a few months ago by someone here asking, "What is really going on in the contour integral for Fourier/Laplace Transforms? Is there rotation in the plane as the integral is computed?" I had the same question when I was in college. I had always tried to learn thoroughly (or, I thought I did). I remember spending days learning as much as I could about derivation of e^x...not in the hand-waving sense, but more deeply. Dirac deltas were a bit hard to swallow without actually understanding, but I said, "Ok..I'll accept it for now. I can actually learn later." Then a couple of teaching assistants got into habit of saying, "So if you sample at twice maximum frequency, you and reproduce signal EXACTLY..". They would make this claim regarding a signal that was clearly NOT band-limted, but where tails in freq domain was so small as to be neglible, but were not zero. This bother me considerably. Then there was the same thing with a u(t)*cos(t) being used as if it were cos(t). While rest of class moved on...I dwelled on this...arrrgg!! Then I started daydreaming about systems that are driven at its real- valued poles, and about the correct physical interpretation (and about relation with zero-input response). But what really depressed me was Fourier theory. The hand-waving was just a little too much. Yes, I'd done transforms in probably 4 or 5 classes prior, but I was not convinced, and that "derivation" that we've all seen in Oppenheim and Willsky conveys a lot of intuition, but..it just felt funny... I'm not ashamed to admit that in one graduate class, were I sat intently thinking, "finally, I'm going to know what's going on with these #*@()! contour integrals and non-analytic functions...", true explanation was skipped as we sped past the fundamental theory and reviewed,YET AGAIN, that #*!*! Fourier pattern table; I was near tears in frustration, until another student who was present saved my sanity by saying, "Don't worry...you're right..there is a lot of hand waving here...no one can really claim to understand this stuff without studying Theory of Distributions." Reference: http://en.wikipedia.org/wiki/Distribution_(mathematics) This made me feel a lot better. At least someone finally acknowledge what I suspected all along: I was ignorant. So 10 years ago I decided to start re-learning things that I was supposed to already know..not so much the math, but the physical intuition of things, and...I guess I can say two things in this regard: 1. Every person who considers himself/herself to be scientist/engineer should take responsibility for the domain, depth, and breadth of what s/he learns. Learning slowly is OK. The end-result is worth the effort. 2. New insight, if it is to be had, requires sustained, unfettered reflection on a subject, and it is OK to not have an answer after 1 day, 2 days, 5 days, 5 months...of thinking. -Le Chaud Lapin-
From: Rune Allnor on 9 Jul 2010 05:14 On 9 Jul, 07:40, Le Chaud Lapin <jaibudu... (a)gmail.com> wrote:> > 1. Every person who considers himself/herself to be scientist/engineer > should take responsibility for the domain, depth, and breadth of what > s/he learns. Learning slowly is OK. The end-result is worth the > effort. One of the few professors I know (the only one?) who I consider worthy of his credentials once said something like "true insight in a handful of well-chosen subjects beat vast amounts of superficial knowledge hands down." I couldn't agree more. > 2. New insight, if it is to be had, requires sustained, unfettered > reflection on a subject, and it is OK to not have an answer after 1 > day, 2 days, 5 days, 5 months...of thinking. Over the past, say, five years I have reached insights on fundamental DSP stuff that I first saw in class some 20 years ago. The properties of the DFT, how to derive the convolution sum formula from scratch - ridiculously basic stuff at the surface. But it took me 15 years to really understand it. Don't know if that says more about me or the subject of DSP... And, interestingly, it took some of the slugfests once common at comp.dsp to force me to contemplate those 'trivial' issues. Rune
From: Jerry Avins on 9 Jul 2010 09:35 On 7/9/2010 5:14 AM, Rune Allnor wrote: > On 9 Jul, 07:40, Le Chaud Lapin<jaibudu... (a)gmail.com> wrote:>> >> 1. Every person who considers himself/herself to be scientist/engineer >> should take responsibility for the domain, depth, and breadth of what >> s/he learns. Learning slowly is OK. The end-result is worth the >> effort. > > One of the few professors I know (the only one?) who I consider > worthy of his credentials once said something like "true insight > in a handful of well-chosen subjects beat vast amounts of superficial > knowledge hands down." > > I couldn't agree more. I agree, but not completely. As a generalist, I have solved practical problems that stumped colleagues more expert than I. My applying what seemed to them unrelated techniques and ideas had them asking "Why didn't I think of that?" >> 2. New insight, if it is to be had, requires sustained, unfettered >> reflection on a subject, and it is OK to not have an answer after 1 >> day, 2 days, 5 days, 5 months...of thinking. > > Over the past, say, five years I have reached insights on fundamental > DSP stuff that I first saw in class some 20 years ago. The properties > of the DFT, how to derive the convolution sum formula from scratch - > ridiculously basic stuff at the surface. But it took me 15 years to > really understand it. Don't know if that says more about me or the > subject of DSP... When a son of mine struggled with integral calculus, I started to review the book techniques the better to help him. I used my old text as a subject guide, but worked through all the techniques on my own. my understanding of some subtleties I had overlooked before was like an epiphany. > And, interestingly, it took some of the slugfests once common at > comp.dsp to force me to contemplate those 'trivial' issues. Yes! Jerry -- Engineering is the art of making what you want from things you can get. �����������������������������������������������������������������������
From: Clay on 9 Jul 2010 10:55 On Jul 8, 3:55 pm, "Nasser M. Abbasi" <n... (a)12000.org> wrote:> I find DSP the hardest subject to become good at. Other students like me > at school also complain how hard the DSP courses are compared to the > other EE courses and other engineering courses in general. > > I think some of the reasons are: > > 1. DSP courses Has the most math. (including complex variables). > 2. Two domains to worry about, time and frequency. Jumping from one to > the other can get confusing. > 3. Two other domains to worry about, continuous time vs. discrete time. > 4. Many relations between many concepts to get right. > 5. One has to also be good in programming. > 6. Demodulation is just hard. Filter design is hard. > 7. Need to also be good in probability and statistics to do random > signals (real life). > 8. Has to know how to do lab work also. Hard stuff. > > And many more. May be you can add more items to the list. > > Do many of the DSP experts here also found DSP hard at school? It seems > only the very smart can become good at DSP. > > I think one is either born to do DSP or not. I think it is genetics. > > --Nasser Some things just take a lot of work. Back when I was young and had learned a lot of engineering stuff on the job, I realized my weak point was math, so I made sure my 1st degree was in math ( I went to school at night after work). Math is necessary for dsp! But once you get math and basic science under your belt, then you have the toolset to apply to dsp or many other disciplines. I learned dsp on my own apart from school, but I made sure I studied the basic stuff well. And like others said, after many years I still find myself learning and reviewing "basic material." Because upon review you will often get new insights that you didn't have the 1st time around. Don't fret that dsp is hard, but look at it as a challenge. If you find it to be fun, then you will continue to learn it. If it is not fun, I hope you can find something that is, because you don't want to go through life doing something you don't like. Clay
From: Joerg on 9 Jul 2010 12:10
steveu wrote: >> On 07/08/2010 02:26 PM, Nasser M. Abbasi wrote: >>> On 7/8/2010 2:07 PM, HardySpicer wrote: >>> >>>> ahhh diddums...you should try some advanced control engineering and >>>> see how you get on. >>>> No sympathy. >>>> >>>> Hardy >>> But DSP and control in a way are interrelated? >>> >>> A filter is just a system. IIR has feedback. Feedback is used in DSP. >>> Using Costas loop (phase-locked loop) in demodulation sues feedback > loop >>> to detect carrier frequency, and I am sure there many other examples. >>> >>> Matlab uses state space approach in converting analog filter to digital >>> filter. Modern control theory is all state space. >>> >>> For me, control/ linear system theory/ signal processing are all very >>> much interrelated. Advanced control theory goes a little more crazy > with >>> advanced math and matrix theory than DSP, but at the end of the day, it >>> is all just a system, with input/output and feedback and fancy >>> disturbances thrown in to make it real. >>> >>> I love to study control theory also, and I also found it very hard. I >>> think control engineers and DSP engineers have the same genetics. >> Real control (forget theory) is about attempting to fit some tractable >> mathematical model to a plant that is -- at root -- viciously nonlinear >> with unknowable dynamics. Many control engineers are so used to doing >> this that they don't even consciously do so -- they use integrator >> anti-windup because "things won't work if I don't", they use >> conservative plant models, etc., -- because at root, it's a nasty, nasty >> problem to solve. > > Isn't a more common case that the plant is pretty well known, and pretty > well linear, but only over a certain range. The tricky stuff is typically > ensuring things don't do wacky if you step outside the well characterised > areas. > No, plants are more like car tires on a dark road, at 32F, it has rained an hour ago and there is a big truck behind you :-) RF can be like that as well if you have to deal with rapidly changing antenna impedances and transistors in the output stage that behave like the princess on the pea. [...] -- Regards, Joerg http://www.analogconsultants.com/ "gmail" domain blocked because of excessive spam. Use another domain or send PM. |