Abstract: A statistical approach can be used to efficiently supply an initial population that provides a good global description of a design space. The SI based simulation can then find a global best design within a reduced number of simulations. The statistical approach can be utilized to determine a plurality of potential best and worst case designs from a design space. The plurality of potential best and worst case designs from the design space seed or prime a SI based simulation. The best case designs are based on design parameters than can be controlled. The worst case designs are based on design parameters than cannot be controlled due. SI based simulations can then be run on the best case designs with respect to the worst case designs to determine probability of failure of the best case design.

Abstract: Identifying an optimized test bit pattern for analyzing electrical communications channel topologies, including: ranking according to channel quality, from worst to best, a set of channel topologies for an electrical communications channel; and for each ranked channel topology beginning with the worst, carrying out the following steps in an iterative loop until a concatenated test bit pattern and a previously optimized test bit pattern are functionally equally fit: concatenating to a previously optimized test bit pattern an additional test bit pattern; optimizing the concatenated test bit pattern values for a next ranked channel in the subset, leaving the optimized values of the previously optimized test bit pattern unchanged; and comparing through use of a fitness function the relative qualities of the previously optimized test bit pattern and the optimized concatenated test bit pattern.

Abstract: A method, system, and computer program product for exploring and optimizing an electrical design space. A computer receiving a design space assigns a plurality of initial values (random or predetermined) for optimizing the design space. A particle swarm containing a plurality of particles is created and an optimization of the design space is then performed using the assigned initial values. Following completion of optimization, the global best and personal best for each particle are updated. Velocity vectors and position vectors of the design space are then updated before the computer performs the optimization process again. The process loops, continually updating global and personal bests and velocity and position vectors until a termination criteria is reached. Upon reaching the termination criteria, the best fitness of each particle of the swarm is assigned as an optimized design space. In an alternate embodiment, the particle with the worst target fitness may be assigned.

Abstract: A statistical approach can be used to efficiently supply an initial population that provides a good global description of a design space. The SI based simulation can then find a global best design within a reduced number of simulations. The statistical approach can be utilized to determine a plurality of potential best and worst case designs from a design space. The plurality of potential best and worst case designs from the design space seed or prime a SI based simulation. The best case designs are based on design parameters than can be controlled. The worst case designs are based on design parameters than cannot be controlled due. SI based simulations can then be run on the best case designs with respect to the worst case designs to determine probability of failure of the best case design.

Abstract: A method, system, and computer program product for exploring and optimizing an electrical design space. A computer receiving a design space assigns a plurality of initial values (random or predetermined) for optimizing the design space. A particle swarm containing a plurality of particles is created and an optimization of the design space is then performed using the assigned initial values. Following completion of optimization, the global best and personal best for each particle are updated. Velocity vectors and position vectors of the design space are then updated before the computer performs the optimization process again. The process loops, continually updating global and personal bests and velocity and position vectors until a termination criteria is reached. Upon reaching the termination criteria, the best fitness of each particle of the swarm is assigned as an optimized design space. In an alternate embodiment, the particle with the worst target fitness may be assigned.

Abstract: Identifying an optimized test bit pattern for analyzing electrical communications channel topologies, including: ranking according to channel quality, from worst to best, a set of channel topologies for an electrical communications channel; and for each ranked channel topology beginning with the worst, carrying out the following steps in an iterative loop until a concatenated test bit pattern and a previously optimized test bit pattern are functionally equally fit: concatenating to a previously optimized test bit pattern an additional test bit pattern; optimizing the concatenated test bit pattern values for a next ranked channel in the subset, leaving the optimized values of the previously optimized test bit pattern unchanged; and comparing through use of a fitness function the relative qualities of the previously optimized test bit pattern and the optimized concatenated test bit pattern.