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Systems of Systems Analysis - Time Series  Systems often contain two or more parameters; these systems are called multivariate. Systems contain parameters defined by models or other means such as measurements from the real world or model simulations that derive parameter values.  Parametric measurements may be limited by sensor noise, response time, quantization errors and other real world factors. In some sampling systems, data samples modeled as noise are filtered out and not further considered in analytic solutions.   Complex coupled systems including platform dynamics, biological systems, financial systems, manufacturing systems are controlled and monitored by design or evolutionary principles. Current analytical methods filter, reduce, simplify, partition models, designs, functions, sensors, monitoring and controllers utilizing first order statistics and simple mathematical formulations that favor stationarity, univariate condition indicators, thresholds, identi...

 

 Idea to IP is not that easy... 1) First the idea -  2) Then 20 steps forward; 10 steps back; 101 steps forward 3) Gap Analysis 4) Competitive Marketplace 5) If Successful how much money is it worth 6) Validation of assessment 7) Getting into the marketplace 8) Gaining customer traction 9) Continue focus 10) MVP 11) Capture the World -  https://simplebabylonjs.herokuapp.com/ 12) Create IP along the way - when you know what's valuable 13) Go look for seed money

Current common Flight Sim software utilize parametric models associated with systems, propulsion elements, aircraft aerodynamics and external forces that generate state/space/time trajectories corresponding to flights.  The outputs from these models are then pushed into Visualization Systems for review and validation of existing aircraft or variants.  JSBSim is a good starting point for many research, development, training and initial designs.  http://jsbsim.sourceforge.net/documentation.html   Deltas between the initial designs occur due to actual flight test dynamics that indicate the prototype models are not sufficient for production usage.  In systems control, the error is the delta between the predicted state parameters and the observed state parameters. In closed loop systems, the error state is used in the feedback state to reduce the error and converge to a desirable state space trajectory.    Larger scale models may include simulated vehicles ...