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    • 1. 发明申请
    • Identifying An Optimized Test Bit Pattern For Analyzing Electrical Communications Channel Topologies
    • 识别用于分析电气通信通道拓扑的优化测试位模式
    • US20100014569A1
    • 2010-01-21
    • US12174349
    • 2008-07-16
    • Moises CasesBhyrav M. MutnuryNavraj SinghCaleb J. Wesley
    • Moises CasesBhyrav M. MutnuryNavraj SinghCaleb J. Wesley
    • H04B17/00
    • H04L43/50
    • 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.
    • 识别用于分析电气通信信道拓扑的优化的测试位模式,包括:根据信道质量进行排序,从最差到最佳,用于电通信信道的一组信道拓扑; 并且对于以最坏情况开始的每个排名的信道拓扑,在迭代循环中执行以下步骤,直到级联的测试位模式和先前优化的测试位模式在功能上是相等的:连接到先前优化的测试位模式,附加测试位 模式; 优化子集中下一个排名的信道的级联测试位模式值,保留先前优化的测试位模式的优化值不变; 并且通过使用适应度函数来比较先前优化的测试位模式和优化的级联测试位模式的相对质量。
    • 2. 发明授权
    • Identifying an optimized test bit pattern for analyzing electrical communications channel topologies
    • 识别用于分析电气通信信道拓扑的优化测试位模式
    • US08327196B2
    • 2012-12-04
    • US12174349
    • 2008-07-16
    • Moises CasesBhyrav M. MutnuryNavraj SinghCaleb J. Wesley
    • Moises CasesBhyrav M. MutnuryNavraj SinghCaleb J. Wesley
    • G01R31/28G06F11/00
    • H04L43/50
    • 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.
    • 识别用于分析电气通信信道拓扑的优化的测试位模式,包括:根据信道质量进行排序,从最差到最佳,用于电通信信道的一组信道拓扑; 并且对于以最坏情况开始的每个排名的信道拓扑,在迭代循环中执行以下步骤,直到级联的测试位模式和先前优化的测试位模式在功能上相等地适合:级联到先前优化的测试位模式,附加测试位 模式; 优化子集中下一个排名的信道的级联测试位模式值,保留先前优化的测试位模式的优化值不变; 并且通过使用适应度函数来比较先前优化的测试位模式和优化的级联测试位模式的相对质量。
    • 3. 发明授权
    • Electrical design space exploration
    • 电气设计空间探索
    • US08453081B2
    • 2013-05-28
    • US12784150
    • 2010-05-20
    • Moises CasesJinwoo ChoiBhyrav M. MutnuryCaleb J. Wesley
    • Moises CasesJinwoo ChoiBhyrav M. MutnuryCaleb J. Wesley
    • G06F17/50
    • G06F17/5063G06F2217/08
    • A method for electrical design space exploration includes receiving a template for an electrical design. Design component parameters associated with at least one component in the electrical design are also received. Weighted factors are assigned to design complexity parameters of the electrical design. The parameters of the complexity can include at least one of following: whether the electrical design is known, a number of the design component parameters, a level of interaction among the design component parameters, a time constraint and a memory restriction of a simulation, and whether a statistical analysis or a worst case approach is used to analyze an output of the simulation. A simulation approach for design space exploration of the electrical design is selected based on the weighted factors for the parameters of the complexity of the electrical design. The simulation is performed based on the selected simulation approach.
    • 电气设计空间探索的方法包括接收电气设计的模板。 还接收与电气设计中的至少一个组件相关联的设计组件参数。 加权因子分配给电气设计的设计复杂性参数。 复杂性的参数可以包括以下至少一个:电气设计是否已知,多个设计组件参数,设计组件参数之间的交互级别,时间约束和模拟的存储器限制,以及 是否使用统计分析或最坏情况的方法来分析模拟的输出。 基于电气设计复杂度参数的加权因子,选择电气设计空间探索的仿真方法。 基于选择的模拟方法进行模拟。
    • 5. 发明申请
    • ELECTRICAL DESIGN SPACE EXPLORATION
    • 电气设计空间探索
    • US20110289463A1
    • 2011-11-24
    • US12784150
    • 2010-05-20
    • Moises CasesJinwoo ChoiBhyrav M. MutnuryCaleb J. Wesley
    • Moises CasesJinwoo ChoiBhyrav M. MutnuryCaleb J. Wesley
    • G06F17/50
    • G06F17/5063G06F2217/08
    • A method for electrical design space exploration includes receiving a template for an electrical design. Design component parameters associated with at least one component in the electrical design are also received. Weighted factors are assigned to design complexity parameters of the electrical design. The parameters of the complexity can include at least one of following: whether the electrical design is known, a number of the design component parameters, a level of interaction among the design component parameters, a time constraint and a memory restriction of a simulation, and whether a statistical analysis or a worst case approach is used to analyze an output of the simulation. A simulation approach for design space exploration of the electrical design is selected based on the weighted factors for the parameters of the complexity of the electrical design. The simulation is performed based on the selected simulation approach.
    • 电气设计空间探索的方法包括接收电气设计的模板。 还接收与电气设计中的至少一个组件相关联的设计组件参数。 加权因子分配给电气设计的设计复杂性参数。 复杂性的参数可以包括以下至少一个:电气设计是否已知,多个设计组件参数,设计组件参数之间的交互级别,时间约束和模拟的存储器限制,以及 是否使用统计分析或最坏情况的方法来分析模拟的输出。 基于电气设计复杂度参数的加权因子,选择电气设计空间探索的仿真方法。 基于选择的模拟方法进行模拟。
    • 9. 发明申请
    • SOLUTION EFFICIENCY OF GENETIC ALGORITHM APPLICATIONS
    • 遗传算法应用的解决方案效率
    • US20090307636A1
    • 2009-12-10
    • US12133480
    • 2008-06-05
    • Moises CasesJinwoo ChoiBhyrav M. MutnuryCaleb J. Wesley
    • Moises CasesJinwoo ChoiBhyrav M. MutnuryCaleb J. Wesley
    • G06F17/50G06N3/12
    • G06F17/505G06F2217/08G06N3/126
    • A method of optimizing a very large scale integrated circuit design takes a circuit description which includes interconnected circuit components and characteristic variables assigned to the circuit components such as environmental, operational or process parameters, computes a first solution for the characteristic variables using a statistical analysis, and then computes a second solution for the characteristic variables using an evolutionary analysis seeded by the first solution. In the exemplary implementation the statistical analysis is a central composite design (CCD) and the evolutionary analysis is a genetic algorithm. Best case and worst case CCD solutions may be used to seed separate genetic algorithm runs and derive global best case and global worst case solutions. These solutions may be compared for sensitivity analysis. The method thereby provides significant reduction in time-to-solution with accurate simulation results.
    • 优化大规模集成电路设计的方法采用包括互连电路组件和分配给诸如环境,操作或过程参数的电路组件的特征变量的电路描述,使用统计分析来计算特征变量的第一解, 然后使用第一个解决方案种子进化的分析计算特征变量的第二个解决方案。 在示例性实施中,统计分析是中心复合设计(CCD),进化分析是遗传算法。 最佳情况和最坏情况CCD解决方案可用于种子分离遗传算法运行,并得出全球最佳情况和全球最坏情况解决方案。 可以将这些解决方案进行灵敏度分析。 因此,该方法通过精确的模拟结果显着减少了解决方案的时间。
    • 10. 发明申请
    • SWARM INTELLIGENCE FOR ELECTRICAL DESIGN SPACE MODELING AND OPTIMIZATION
    • 电气设计空间建模与优化的SWARM智能
    • US20100229131A1
    • 2010-09-09
    • US12398535
    • 2009-03-05
    • Moises CasesJinwoo ChoiBhyrav MutnuryNavraj SinghCaleb J. Wesley
    • Moises CasesJinwoo ChoiBhyrav MutnuryNavraj SinghCaleb J. Wesley
    • G06F17/50
    • G06F17/5045G06F2217/08
    • 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.
    • 一种用于探索和优化电气设计空间的方法,系统和计算机程序产品。 接收设计空间的计算机分配用于优化设计空间的多个初始值(随机或预定)。 产生包含多个粒子的粒子群,然后使用分配的初始值来执行设计空间的优化。 在优化完成后,更新每个粒子的全球最佳和个人最好的。 然后在计算机再次执行优化处理之前更新设计空间的速度向量和位置向量。 过程循环,持续更新全局和个人最佳状态以及速度和位置向量,直到达到终止标准。 达到终止标准后,群体的每个粒子的最佳适应度被指定为优化的设计空间。 在替代实施例中,可以分配具有最差目标适应度的粒子。