Concerning the first issue, there are the trade–off between the
accuracy and hardware cost in case of in- vestigating LFSR–based PRNGs:
classical LFSR approach, multiple LFSRs approach and Leap–Ahead LFSR
approach. The third one give the generation of SNs in parallel, and
consume less hardware than others. Meanwhile, SNGs relying on CA–based
PRNG with the good features of CA provide an out- standing quality
compared the previous approaches, however, this technique requires more
complexity in hardware configuration. Furthermore, there are the methods
that using a number of PRNG and basic logic elements to generate SNs
with a considerable accuracy. Besides, FSM has recently investi- gated
in SC, hence, a synthesis approach in condition of random source
limitation was also analysed in our work.
While SNGs are the most important problem in SC, stochastic operators
equally play an essential role in this system. First, the stochastic
basic elements which was early proposed such as AND gate, XNOR gate, MUX
which consume less hardware in carrying out the unsigned multiplication,
signed multiplication, scaled adder, respectively in conventional
computing. Furthermore, FSM–based stochastic elements have proved their
outstanding characteristics in carrying out the complexe functions as
tanh, absolute, exponential exponentiation on absolute value. Besides,
based on the previous works, we also develope the triple-length
LFSR based Stochastic scale adder which can be give a new way to
implement the scale addition in SC.
Our work investigated the above stochastic operators in image processing
applications. The first one, edge detection was accomplished by using
two operators: Roberts and Prewitt. According to the
received results, it can be shown that SC with its simplicity in
hardware architecture can give the output as good as that of
conventional computing. For the second operator, noise reduction based
on median filter equally yields the results of high quality. The
simulation on different lengths of this operator is also executed, and
as expected, the accuracy and precision increase steadily with
stochastic sequence length. This part ended by evaluating the
faul–tolerant capacity of SC in comparison with traditional approach.
Our experiments presented a slow change in stochastic design to
manufacturing process variations and soft errors, while conventional
computing is very sensitive with such changes. Although due to the
requirement of a large number of bits to represent, it is evident to see
that SC consumes more energy compared traditional approaches, it might
be the amenable choice when the transient circuit variations are
present.
SC, an unconventional computing which exploits the probabilistic aspect
of traditional technologies, brings a new way which is effective in some
applications where uncertainty is considered. It can be seen as a method
of simple hardware implementation and high fault tolerance. However, the
accuracy and processing time are the main problems which are still
poorly understood. Therefore, the following issues might be taken into
account in the future:
To sum up, SC has the outstanding features which can adapt to the
current technology trends where the uncertainty in circuit behavior
becomes more interesting than ever. It will definitely lead to
long–term study in the future.
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