By Weng W. Chow, Stephan W. Koch
This in-depth name discusses the underlying physics and operational rules of semiconductor lasers. It analyzes the optical and digital houses of the semiconductor medium intimately, together with quantum confinement and gain-engineering results. The textual content additionally comprises fresh advancements in blue-emitting semiconductor lasers.
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Additional info for Semiconductor-Laser Fundamentals: Physics of the Gain Materials
Example text
In the case of the PCNN almost all of the cost of computation stems from the interconnection of the neurons. In many implementations users set M = W which would cut the computational needs in half. One method of reducing the costs of computation is to make an efficient algorithm. 5 in which a smoothing operation replaced the traditional Gaussian type connections. Another method is to reduce the number of connections. What is the minimum number of neurons required to make an operable system? This question is answered by building a minimal system and then determining if it created autowave communications between the neurons [18].
Activity from one region can so drastically alter the activity in another region that object recognition becomes very difficult. The solution to this problem is to alter the connections to the neurons so that they become sensitive to previous pulsing steps. In the model presented, these connections are described as centripetal autowaves such that the wave front progresses towards the local centre of curvature of the pulsing regions. This eliminates the ever-expanding nature of the waves without altering their shape-describing form.
An example of the results from a PCNN with a FPF is shown in Fig. 14. Three different masks are shown together with a cut in the correlation matrix. The top row uses a ‘hand-tailored’ mask and yields a strong correlation. A more ‘diffuse’ mask (second and third row) will still yield strong correlations, in particular if several images are considered. 7 Target Recognition – Binary Correlations One application of the FPF is to find targets in an image. In this case a single image is used for the recognition of the target and the fractional power term is adjusted to increase the importance of edge information.