Abstract: Signal-processing devices having memristors are described for performing frequency-discrimination functions, amplitude-discrimination functions, and time-oriented functions. In each case, the time-domain behavior of the memristors described herein enables these functions to be performed. In one embodiment, memristance of an arrangement of memristors of a device is, after an initial transitional period, predominantly at a first level if frequency of an input signal of the device is less than a first frequency and predominantly at a second level if the frequency of the input signal is greater than a second frequency.

Abstract: Signal-processing devices having memristors are described for performing frequency-discrimination functions, amplitude-discrimination functions, and time-oriented functions. In each case, the time-domain behavior of the memristors described herein enables these functions to be performed. In one embodiment, memristance of an arrangement of memristors of a device is, after an initial transitional period, predominantly at a first level if frequency of an input signal of the device is less than a first frequency and predominantly at a second level if the frequency of the input signal is greater than a second frequency.

Abstract: Signal-processing devices having memristors are described for performing frequency-discrimination functions, amplitude-discrimination functions, and time-oriented functions. In each case, the time-domain behavior of the memristors described herein enables these functions to be performed. In one embodiment, memristance of an arrangement of memristors of a device is, after an initial transitional period, predominantly at a first level if frequency of an input signal of the device is less than a first frequency and predominantly at a second level if the frequency of the input signal is greater than a second frequency.

Abstract: A method and apparatus for the automatic creation of novel designs, specifically electronic circuits, controllers, antennas, and mechanical systems to satisfy prespecified design goals, using search procedures, such as genetic programming, genetic algorithms, simulated annealing and hill climbing is described. Further, the techniques include automatically creates designs which do not posses key characteristics of preexisting technology. The present invention uses a population of entities which may be evolved to generate structures that may potentially satisfy the design goals. The behavior of the structures is evaluated in view of the design goals, and the structures are compared to a preexisting structure. Those structures more closely meeting the design goals and not similar to the preexisting structure are favored further until a structure is generated that either meets the prespecified design goal or some other process completion criteria. In this manner, a novel structure may be obtained.

Abstract: Signal-processing devices having memristors are described for performing frequency-discrimination functions, amplitude-discrimination functions, and time-oriented functions. In each case, the time-domain behavior of the memristors described herein enables these functions to be performed. In one embodiment, memristance of an arrangement of memristors of a device is, after an initial transitional period, predominantly at a first level if frequency of an input signal of the device is less than a first frequency and predominantly at a second level if the frequency of the input signal is greater than a second frequency.

Abstract: A general automated method for synthesizing the design of both the topology and parameter values for controllers is described. The automated method automatically makes decisions concerning the total number of signal processing blocks to be employed in the controller, the type of each signal processing block, the topological interconnections between the signal processing blocks, the values of all parameters for the signal processing blocks, and the existence, if any, of internal feedback between the signal processing blocks within the controller. The general automated method can simultaneously optimize prespecified performance metrics (such as minimizing the time required to bring the plant outputs to the desired values as measured by the integral of the time-weighted absolute error or the integral of the squared error), satisfy time-domain constraints (such as overshoot, disturbance rejection, limits on control variables, and limits on state variables), and satisfy frequency domain constraints (bandwidth).

Abstract: Skill games are described that are implemented using network communications. The subject matter of the present invention concerns games of skill that are legal, under current law, in most states of the United States and in many jurisdictions of other countries and the game includes a mechanism for determining if a player is eligible.

Abstract: An apparatus is provided for controlling a system to achieve a specified response. In one embodiment, the apparatus is a proportional, integrative, and derivative (PID) controller having a proportional element, an integrative element, and a derivative element coupled together. The elements respond to a reference signal and generate a control signal that causes a plant to generate a plant output. The proportional element has a gain element where the gain is a function of the ultimate gain of the plant (Ku) and the ultimate period of the plant (Tu). The controllers may also be embodied in non-PID controllers that share common elements, such as the use of: (a) Astrom-Hagglund controller output as an input for a subsequent controller; (b) internal feedback; and (c) a subsequent controller that performs a subtraction operation to generate the difference between the output of the Astrom-Hagglund controller and the output of the subsequent controller.

Abstract: Skill games are described that are implemented using network communications. The subject matter of the present invention concerns games of skill that are legal, under current law, in most states of the United States and in many jurisdictions of other countries and the game includes a mechanism for determining if a player is eligible.

Abstract: A general automated method for synthesizing the design of both the topology and parameter values for controllers is described. The automated method automatically makes decisions concerning the total number of signal processing blocks to be employed in the controller, the type of each signal processing block, the topological interconnections between the signal processing blocks, the values of all parameters for the signal processing blocks, and the existence, if any, of internal feedback between the signal processing blocks within the controller. The general automated method can simultaneously optimize prespecified performance metrics (such as minimizing the time required to bring the plant outputs to the desired values as measured by the integral of the time-weighted absolute error or the integral of the squared error), satisfy time-domain constraints (such as overshoot, disturbance rejection, limits on control variables, and limits on state variables), and satisfy frequency domain constraints (bandwidth).

Abstract: A general automated method for synthesizing the design of both the topology and parameter values for controllers is described. The automated method automatically makes decisions concerning the total number of signal processing blocks to be employed in the controller, the type of each signal processing block, the topological interconnections between the signal processing blocks, the values of all parameters for the signal processing blocks, and the existence, if any, of internal feedback between the signal processing blocks within the controller. The general automated method can simultaneously optimize prespecified performance metrics (such as minimizing the time required to bring the plant outputs to the desired values as measured by the integral of the time-weighted absolute error or the integral of the squared error), satisfy time-domain constraints (such as overshoot, disturbance rejection, limits on control variables, and limits on state variables), and satisfy frequency domain constraints (bandwidth).

Abstract: The present invention is a genetic programming problem solver that automatically generates computer programs to solve problems. The genetic programming problem solver incorporates architecture-altering operations. In one embodiment, the genetic programming problem solver uses architecture-altering operations for automatically defined functions and loops, together with indexed memory, to generate the resulting computer programs. In a second embodiment, the genetic programming problem solver uses architecture-altering operations of automatically defined function, loops, recursions, and stores to generate the resulting computer programs.

Abstract: The present invention consists of a method and apparatus for the automatic creation of the topology, component sizing, placement, and routing of complex structures, such as electronic circuits or mechanical systems, to satisfy prespecified high-level design goals. The present invention uses a population of entities which are evolved over a series of generations by an iterative process involving the application of operations, such as mutation, crossover, reproduction, and architecture-altering operations. The individuals in the population are each developed, in a developmental process, into a structure that may potentially satisfy the design goals. The present invention also determines the placement of components within the developing structure and determining the routing of the connecting means (wires for electrical circuits) between the components.

Abstract: An automated design process and apparatus for use in designing complex structures, such as circuits, to satisfy prespecified design goals, using genetic operations. The present invention uses a population of entities which may be evolved to generate structures that may potentially satisfy the design goals. The behavior of such generated structures is evaluated in view of the design goals, and those structures more closely meeting the design goals are evolved further until a structure is generated that either meets the prespecified design goal or some other process completion criteria. In this manner, a design complex structure may be obtained.

Abstract: An apparatus and method for solving problems where a population is created and evolved to generate a result. While solving the problem, the architecture of entities in the population are altered. Each of said entities may include internally and externally invoked sub-entities. The externally invoked sub-entities are capable of having actions, invocations of sub-entities which are invoked internally, and material. Also, each sub-entity which is invoked internally is capable of including actions, invocations of internally invocable sub-entities, material provided to the externally invocable sub-entity, and material.

Abstract: An automated design process and apparatus for use in designing complex structures, such as circuits, to satisfy prespecified design goals, using genetic operations. The present invention uses a population of entities which may be evolved to generate structures that may potentially satisfy the design goals. The behavior of such generated structures is evaluated in view of the design goals, and those structures more closely meeting the design goals are evolved further until a structure is generated that either meets the prespecified design goal or some other process completion criteria. In this manner, a design complex structure may be obtained.

Abstract: An apparatus and method for solving problems where a population is created and evolved to generate a result. While solving the problem, the architecture of entities in the population are altered. Each of said entities may include internally and externally invoked sub-entities. The externally invoked sub-entities are capable of having actions, invocations of sub-entities which are invoked internally, and material. Also, each sub-entity which is invoked internally is capable of including actions, invocations of internally invocable sub-entities, material provided to the externally invocable sub-entity, and material.

Abstract: An apparatus and process for solving problems using self-replicating and self-improving entities. The present invention includes an apparatus and process for solving a problem using a population of entities, wherein each of the entities is an arrangement of actions and material which are capable of including an incorporation action and are capable of including an emission action. The present invention also includes a process and apparatus for activating each of the entities by presenting each of the entities with at least one combination of environmental material. If an entity has an incorporation action then that entity searches the population for a part of one of the entities and then incorporates the portion of the one entity associated with the part into itself.

Abstract: An apparatus and method for solving problems using automatic function definitions, for solving problems using recursion and for performing data encoding. The present invention includes an apparatus and process for creating a population and then evolving that population to generate a result. When solving problems using automatic function definition, the apparatus and process initially creates a population of entities. Each of said entities has sub-entities of internally and externally invoked sub-entities. The externally invoked sub-entities are capable of having actions, invocations of sub-entities which are invoked internally, and material. Also, each sub-entity which is invoked internally is capable of including actions, invocations of internally invocable sub-entities, material provided to the externally invocable sub-entity, and material. The population is then evolved to generate a solution to the problem.

Abstract: A non-linear genetic process for problem solving using co-evolving populations of entities is disclosed. The iterative process of the present invention operates on a plurality of populations of problem solving entities. First, an activated entity in one of the plurality of populations (evolving population) performs, producing a result. The result is assigned a value and the value is associated with the producing entity. The value assigned is computed relative to the performance of the entity in a population different from the evolving population (one of the environmental populations). Next, entities having relatively high associated values are selected from the evolving population. The selected entities perform either crossover or fitness proportionate reproduction. In addition, other operations such as mutation, permutation, define building blocks and editing may be used. Next, the newly created entities are added to the evolving population.