Tiling algorithm

Neural network architectures and learning algorithms (see Table 9.1) GA = genetic Algorithm tiling = tiling algorithm. 

Figure 3. Typical random ST tiling grown using an algorithm described in Section V.B.

Fig. 12 Time-frequency domain tiling for the pyramid algorithm, (a) First application of a pair of filters to 16-point signal (h) the filters applied to the low-frequency part of (a) (c) and (d) further cut up of the lower frequencies analogous to (h).

Hazard analysis using STPA will identify application-specific safety design constraints that must be enforced by the control algorithm. For the thermal-tile processing robot, a safety constraint identified above is that the manipulator arm must never be extended if the stabilizer legs are not fully extended. Causal analysis (step 2 of STPA) can identify specific causes for the constraint to be violated and design features can be created to eliminate or control them. 

The arrays described in the last section are all periodic arrays. Winfree suggested that DNA molecules can be assembled in arrays based on algorithms more complex than simple periodicity. Thus, in principle, the self-assembly of DNA tiles can be used to generate complex arrangements, without using a unique tile for every component of the asyininetric unit. A preliminary test of this notion has been executedJ in which a onedimensional cumulative exclusive OR (XOR) calculation was performed over four steps with high accuracy. 

This scheme works the other way around. Here, the tiles are sequentially processed on a fixed-size array that executes the operations of a single tile in parallel. It needs memory external to the array to store data for another tile. Typically, LPGS is used to execute huge and parametrized algorithms on a relatively small and fixed size array. 

The first demonstration of these ideas—two-dimensional, periodic arrays of DNA tiles—could hardly be called algorithmic, but it did show that the se-... 

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