Ms.P.Revathi,M.Sc.,M.Phil.,
Assistant
Professor,
Department of Computer
Science,
Marudhar Kesari JainCollege,
Vaniyambadi,[Vlr
DT],TamilNadu
Revathipriya50@gmail.com
_______________________________________________________________
Before the digital revolution, image and signal processing was
performed using analog circuitry. Today digital signal processing (DSP) has
defined our lives. Although some mixed-signal designs are of current interest,
DSP dominates everything that we own or use everyday. DSP chips exist in many
devices such as our cell phones, our iPods, our wireless router, our new HDTV.
The purpose of this paper is to consider
possibilities of DSP outside the semiconductor or electronic domain. Organic
elements (such as DNA and polymers) that conduct electricity can be used to
build organic semiconductors at the molecular level [1]. However, more fundamental
questions can be asked. Can DSP be performed in exotic materials, such as
chemical substrates, cells, organisms, or even DNA, without the use of
electrical currents? Will we be able to build fully blown DSP systems out of
these materials? Or will some DSP functions (such as storage and data
archiving) be implemented with such materials? We do not attempt to provide a
thorough scientific review of such
II. Chemical based dsp
There has been an extensive amount of research on reaction-diffusion
media, which are implementations of chemical oscillators. Chemical oscillators
are systems of chemical reac-tions that exhibit oscillatory behavior when not
in the equilibrium state. The concentration of reagents and products varies
over time. A certain category of those are light-sensitive and can store input
information during long periods of time. When stimulated by light and
controlled by the acidity
of the medium (mixture of chemical compounds), basic or complex
image transformations such as contour enhancement, image segmentation, image
half toning, and others can be achieved (see [2, ch. 3, 4]). The mathematics
behind the above processes are systems of nonlinear differential equations.
Although nonlinear image processing with computers is not new, it is extremely
fascinating to see
chemical media perform complicated image-processing tasks in a short
period of time.
III. Organism Based Dsp
The beautiful colors found in Impressionistic paintings were the
result of scientific discovery of novel pigments But sometimes art can drive
scientific evolution. Take, for example, the
artist/scientist Cameron Jones from Australia. He used fungi to
process audio signals. He recorded music on compact discs (CDs) and then used
the CDs as substrates to grow fungi. He put the CDs in his CD player and
watched how the optically recorded sound was distorted by the fungi.
Surprisingly the fungus growth pat-terns were dependent on the optical grooves
recorded on the CD. The fungi were reacting to the recorded information. The
audio track was Bprocessed[ by the grown fungus. This interface of optics and
biomaterials was a clear demonstration that signal processing can be performed
with other means.
Going into a smaller scale, individual
proteins can be used to perform processing. For example, protein-based memories
utilize the light sensitivity of a special category of proteins. A protein that
is often used is bacteriorhodopsin. This protein is found in the bacterium
Halobacterium halobium, which thrives in environments with high salt and low
oxygen concentration. If oxygen levels drop, the purple membrane of the bacterium
grows to expose bacteriorhodopsin. The protein converts light into energy by
pumping a proton through the membrane, creating a chemical and osmotic
potential. This cycle can be repeated millions of times, and the protein can
survive high tempera-tures. In a few words, the protein is an excellent medium
for storing information, since it can last a long time and has rewritable
abilities and truly nanoscale size. A film of the protein can be deposited as a
layer on an appropriate substrate. Light expo-sure, via direct light or laser,
can be used to stimulate the protein and thus record the input light
information (could be an image). Information can be read out using a laser as
well.
The fact that biological materials are
used for storage opens the door to a unique method of material optimiza-tion.
Although such optimization is complex and requires extensive knowl-
edge of the substance’s properties, evolution through genetic modifica-tions
can be used to generate altered versions of the substance. Each out-come can be
tested for its performance, and new and improved generations of substances can
be further generated as mutations of the previous outcomes.
In fact, this has happened already.
Light-sensitive proteins are taken from one bacterium and are placed in more
Bprogrammable[ bacteria such as E.coli (since its genetic code has been studied
longer). Synthetic biology is doing exactly this. It modifies the genetic code
of organ-isms to add Bnovel[ functionality, such as light responsivity, NOT,
AND, and OR gates. There is a lot of activity in this area with conferences and
dedicated journals, and an established database of standard biological parts
(BioBricksTM). There is even a com-petition (the International
Genetically Engineered Machine Competition) where students compete in
design-ing biological systems that can per-form simple computations. In the
2005 competition, students made a biofilm (layer) of bacteria that could perform
distributed edge detection on an image. E.coli cells were modified to react to
light using a light-sensing protein and change their state accord-ing to their
neighbor cells. All the needed parts were taken from the bio-Bricks database.
As a result, the edges of a projected image were found. In another example [3],
E.coli was mod-ified in a similar fashion to store image data with a
theoretical resolution of 100-Mpixels/in2 (or 108 bacteria/in2).
An image was projected to the bacteria layer and read using a weak laser.
IV. Dsp With DNA
Similarly, logic circuits can be built using just DNA molecules. The
DNA double helix is made from two single strands of DNA, each of which is a
sequence from the quaternary alphabet (A,T,G,C). The two single strands are
held together due to hybridization of the complementary sequences. A
com-plement sequence of a strand is the one found by performing the
Watson–Crick complement rule (A-T, G-C). Using DNA strands as input and
processing elements, the simple hybridization force can act as a powerful
computa-tional tool. The sequence of input and processing strands can be
designed in such a way that their hybridization can be predicted and
controlled. Using this basic principle, complex molecular structures and basic
arithmetic opera-tions can be performed. DNA comput-ing is the field that
utilizes DNA to perform computation.
The literature abounds with
de-monstrations of DNA circuits that behave like transistors and adders and
point to the future when complex DNA circuits acting as digital filters are
realizable. For example, Winfree’s group at Caltech presented a method for the self-assembling computation of the
Sierpinski triangle [4]. DNA single strands hybridize with each other to form
tiles (building blocks) that self-assemble to build complex structures (like
the triangle). They described the correlation between the Sierpicski
triangle and the binary version of wavelet and Fourier trans-forms, as well as
the Hadamard trans-form. Self-assembly and tiling can also be used to study
Markov fields, which have been extensively used in image processing. In the
future, one can imagine a self-assembly approach to image processing following
similar principles. The same group has demonstrated a hybridization-only [5]
and entropy driven [6] protocols for implementing logical gates, signal
restoration, amplification, cascade, and feedback, thus developing DNA-based
logical circuits. Such development brought us closer to the possible
realization of DNA-based DSP circuits.
V . C O N C L U S I O N
If we were allowed to be as to offer a
prediction for the future, we believe that the turning point in the organic
future of DSP is to see which technology, from the aforementioned or from the
ones to come, will allow for the implementation of a fast Fourier transform
combined with elegant and not tedious input–output procedures. We believe that
DNA-based logical circuit design will mate-rialize first followed by synthetic
gene networks. DNA exploration is driven by two large forces: i) human
sustain-ability, as in understanding organism formation, development,
evolution, and function, and hence finding cures for diseases, and ii)
engineer-ing curiosity, as in trying to utilize DNA and genes to do
computations. This has led to a growth and cost reduction similar to that
witnessed by the semiconductor industry (see Moore’s law). The cost and
delivery time of DNA synthesis is being reduced exponentially, thus making data
input elegant and economical. DNA sequencing, replication, and filtering are
getting cheaper and faster everyday, having a similar effect on data output.
For example, sequencing the human genome the first time took ten years and a
couple of billion dollars. Now there exist commercially available sequencers
(for example, from 454 Life Sciences) that can do it in months at a fraction of
the cost, with prospects to reduce it to days and below $1000, as set by The
$1000 Genome Project and the re-cently announced X-Prize. DNA equip-ment is
getting even smaller, considering, for example, NEC’s porta-ble DNA lab in a
briefcase, and cheaper, such that anybody can process the signals in the office
and later at home pull out their Discovery’s DNA Explorer Kit or CSI’s DNA Lab
Kit and with their kids (or alone satisfying their inner child) manipulate and
ana-lyze DNA in their living room.
References
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J. M. Seminario, L. Yan, and Y.
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[4]
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