The concept of processing interesting signals is not new. It has been around as long as we, as humans, have recognized we could manipulate the world around us to make life easier. If I quickly review the last century with respect to signal processing, I can split it into an era of analog signal processing superseded by the present era of digital signal processing. The event that caused this abrupt move from analog to digital signal processing was the invention of the microprocessor followed by the invention of the digital signal processor. 

The success of the digital era of signal processing of which we are presently in has to do with:

1. Advancements made in the theory of signal processing
2. The creation and advancements of the digital signal processor
3. The applications of signal processing theory and the digital signal processing elements 

We now seem to be at the end of the road. But the good news is that new applications begging for signal processing solutions have continued to expand. Unfortunately both the theory and processing capability have lagged the opportunities. Specifically, the raw performance of the signal processor has lagged and the body of signal processing theory has seemed to have not found ways around the hardware lag.

The issue with the signal processor hardware is that the digital processor architectures do not provide enough raw performance to tackle the new opportunities. And when enough raw performance is assembled, the resulting power dissipation becomes problematic, not to mention significant cost issues. 

But these are exciting problems as they motivates us as researchers and industrialists to explore new avenues. Or as I put it, we are asking ourselves new questions for which there are no answers – at least no answers yet. One interesting area to explore requires us to look back rather than forward. That is, can we revisit the world of analog signal processing to make that next advancement? Aha, the first question which has no answer.

Now for a bit of history. Analog computing was a casualty of the digital computer. Specifically around about 1970 when the microprocessor was invented. This was followed about a decade later with the invention of the digital signal processor (DSP). The digital revolution permanently eliminated the need for analog computers (note I have said “analog computers” rather than “analog signal processing”).   

We (yes I was one of them) in the world of DSP convinced the industrial and academic worlds that there was no longer a need for analog as digital computational elements could solve all of the problems that existed in an analog processing system: 

1. Noise
2. Accuracy
3. Dynamic range
4. Linearity
5. Ease of programming
6. Reliability

But it is time we revisit the world of analog computing. There have been amazing advancements made in signal processing theory and in integrated circuit technology. But it seems we are conducting ourselves similar to that of a junior high dance where the signal processing people are on one side of the gym and the IC architects are on the other side of the gym.  But no one wants to walk across the gym and ask someone to dance.  The amazing aspect of this picture is the rapidly expanding new applications that are begging the two groups to dance with each other, but no one is making the first move. 

A few months ago I was on a panel discussion at the International Conference on Acoustics, Speech and Signal Processing (ICASSP). It is the premier IEEE conference on signal processing.  My opening remarks were on this subject. My goal was to get the signal processing research community away from their wall in the gym and begin to solve the issues related to an analog signal processing element. The obvious next move is to try to pry the IC architects away from their wall in the gym.

With this mental picture in mind, let me put the technology in perspective. It is the multiply function which limits both the raw performance of signal processing and the battery life of the DSP.  A cursory comparison of an analog multiplier to a digital multiplier suggests that the raw performance of an analog multiplier could be many orders of magnitude higher in raw performance while giving at the same time several orders of magnitude lower power dissipation. In addition, the purchase and operational cost could be significantly lower.  It all seems too good to be true.

But we won’t return to analog processing concepts until we resolve the problems associated with analog signal processing that I mentioned previously.

So, the challenge is, in light of new applications that need higher performance at lower power dissipation, can we, with today's integrated circuit technology, resolve the problems inherent to analog signal processing? If so, we can be at the start of a new era of explosive growth of new applications that signal processing enables.

My answer to the challenge is a resounding “yes we can” if we can get the dance started.

eletter-08-28-2018

eletter-08-27-2018