The MIT Geophysical Analysis Group (GAG) from inception to 1954

Geophysics ◽  
2005 ◽  
Vol 70 (4) ◽  
pp. 7JA-30JA ◽  
Author(s):  
Enders A. Robinson

The beginning of digital signal processing took place in the years 1950 to 1954. Using an econometric model, E. A. Robinson in 1951 came up with the method of deconvolution, which he tested on 32 seismic traces. Norbert Wiener, George Wadsworth, Paul Samuelson, and Robert Solow were his advisors. On the basis of this work, the MIT president's office in 1952 set up and sponsored the Geophysical Analysis Group (GAG) in the Department of Geology and Geophysics. GAG was made up of graduate students doing research in digital signal processing. In 1953, a consortium of oil and geophysical companies took over the sponsorship. At first, GAG used the MIT Whirlwind digital computer. In order to do the larger amount of computing required by the consortium, the Computer Service Section of Raytheon Manufacturing Company was enlisted in 1953. The Raytheon people who played key roles were Richard Clippinger, Bernard Dimsdale, and Joseph H. Levin, all of whom had worked on ENIAC, the world's first electronic digital computer. As originally built, ENIAC did not use programs stored in memory as does a modern computer; instead, the programming was done by rewiring the physical components for each new problem. In 1948, Clippinger was responsible for converting ENIAC into the world's first operational stored-program computer. ENIAC had 20 accumulators but no other random access memory (RAM). The programs were stored in the function tables, which acted as programmable read-only memory(PROM). For GAG work in 1953, Raytheon used the British Ferranti Mark 1 computer (which was the commercial version of the Manchester Mark 1 computer, for which Alan Turing played a key role). This computer was installed at the University of Toronto to help in the design of the St. Lawrence Seaway. Raytheon was plagued by frequent breakdowns of the computer but still produced several hundred seismic deconvolutions for the summer GAG meeting in 1953. The consortium was pleased with the geophysical results but was disheartened by the unreliability of the current state of digital technology. As a result, GAG was directed to find analog ways to do deconvolution. Instead, GAG found that all of the analog methods, and in particular, electric frequency filtering, could be done by digital signal processing. In fact, the digital way provided greater accuracy than the analog way. At the spring meeting in 1954, GAG proposed that all analog processing be thrown out and replaced by digital signal processing. Raytheon was at the meeting and offered to obtain or build all the elements required for digital signal processing, from input to output. The conversion to digital was not done at the time. However, that step did happen in the early 1960s, and exploration geophysics has the distinction of being the first science to experience a total digital revolution. Digital processing today provides seismic images of the interior of the Earth so startling that they compare to images of the stars made by the Hubble telescope. (In fact, the digital method of deconvolution first developed in geophysics made possible the digital correction of the lens of the Hubble telescope.)

2012 ◽  
Vol 241-244 ◽  
pp. 1751-1755
Author(s):  
Yin Bing Zhu ◽  
Ke Jing Cao ◽  
Bao Li

Auto-search is one of the key steps in digital signal processing for Loran-C receivers, however, for digital sampling Loran-C signal, the principle search algorithm is unable to realize signal search veraciously because of the asynchronism between sampling clock and transmitting station clock. For this question, an auto-search algorithm based on subsection correlation for Loran-C is presented after analyzing the principle search algorithm. The experiment results show that for the received digital Loran-C signal, there are several correlation and accumulation values of master and secondary stations to exceed the search thresholds; the maximum correlation and accumulation value of the presented algorithm is far higher than that of the principle algorithm. That is to say, the presented algorithm can search the arrival time of master and secondary station successfully, solve the problem of clock asynchronism effectively, and enhance the search sensitivity of the receiver, which have great significance for digital processing of Loran-C signal and the engineering realization of Loran-C digital receiver.


2009 ◽  
pp. 53-68
Author(s):  
Terrence D. Lagerlund

This chapter reviews the principles of digitization, the design of digitally based instruments for clinical neurophysiology, and several common uses of digital processing, including averaging, digital filtering, and some types of time-domain and frequency-domain analysis. An understanding of these principles is necessary to select and use digitally based instruments appropriately and to understand their unique features.


Geophysics ◽  
2005 ◽  
Vol 70 (4) ◽  
pp. 5JA-5JA ◽  

In the following two articles — part of a series of Geophysics articles published in 2005 to mark the 75th anniversary of SEG — Enders Robinson and Sven Trietel revisit the early development of digital signal processing (DSP) in the Geophysical Analysis Group (GAG) at Massachusetts Institute of Technology.


2019 ◽  
pp. 34-39 ◽  
Author(s):  
E.I. Chernov ◽  
N.E. Sobolev ◽  
A.A. Bondarchuk ◽  
L.E. Aristarhova

The concept of hidden correlation of noise signals is introduced. The existence of a hidden correlation between narrowband noise signals isolated simultaneously from broadband band-limited noise is theoretically proved. A method for estimating the latent correlation of narrowband noise signals has been developed and experimentally investigated. As a result of the experiment, where a time frag ent of band-limited noise, the basis of which is shot noise, is used as the studied signal, it is established: when applying the Pearson criterion, there is practically no correlation between the signal at the Central frequency and the sum of signals at mirror frequencies; when applying the proposed method for the analysis of the same signals, a strong hidden correlation is found. The proposed method is useful for researchers, engineers and metrologists engaged in digital signal processing, as well as developers of measuring instruments using a new technology for isolating a useful signal from noise – the method of mirror noise images.


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