OCME · Bilingual mathematics & derivations
Second Applied Foundations: Representation, Assessment Records, Periodicity, Initial Values, Bisection, Linear Programming and Capacity-Limited Growth
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- Variables and algebraic expressions
- Function mapping
- Coordinate plane
- Proposition
- Counterexamples and domain eligibility
- Discrete-time dynamical system
- Sequence
- Equation
- Ordinary differential equation
- Domain, codomain, and range
- Numerical approximation and error
- Point values and continuity of real functions
- Usual order on the real numbers
- Optimization problem
- Linear equation in one variable
- Linear systems in two variables and degenerate constraints
- Plane vectors in a fixed basis
- Discrete exponential growth model
- Arithmetic operations
- Mathematical representation
- Diagnostic mathematical assessment records
- Orbits, fixed points and periodic points
- Initial-value problem
- Finite sign-bracket updates in the bisection method
- Linear programming
- Discrete logistic increment model
Complete seven traceable knowledge objects in dependency order on the existing number-system and function foundations.
This is a suggested learning sequence, not a universal logical dependency or a formal proof.
Variables and algebraic expressions
Existing canonical prerequisite for the new objects in this pulse.
Function mapping
Existing canonical prerequisite for the new objects in this pulse.
Coordinate plane
Existing canonical prerequisite for the new objects in this pulse.
Proposition
Existing canonical prerequisite for the new objects in this pulse.
Counterexamples and domain eligibility
Existing canonical prerequisite for the new objects in this pulse.
Discrete-time dynamical system
Existing canonical prerequisite for the new objects in this pulse.
Sequence
Existing canonical prerequisite for the new objects in this pulse.
Equation
Existing canonical prerequisite for the new objects in this pulse.
Ordinary differential equation
Existing canonical prerequisite for the new objects in this pulse.
Domain, codomain, and range
Existing canonical prerequisite for the new objects in this pulse.
Numerical approximation and error
Existing canonical prerequisite for the new objects in this pulse.
Point values and continuity of real functions
Existing canonical prerequisite for the new objects in this pulse.
Usual order on the real numbers
Existing canonical prerequisite for the new objects in this pulse.
Optimization problem
Existing canonical prerequisite for the new objects in this pulse.
Linear equation in one variable
Existing canonical prerequisite for the new objects in this pulse.
Linear systems in two variables and degenerate constraints
Existing canonical prerequisite for the new objects in this pulse.
Plane vectors in a fixed basis
Existing canonical prerequisite for the new objects in this pulse.
Discrete exponential growth model
Existing canonical prerequisite for the new objects in this pulse.
Arithmetic operations
Existing canonical prerequisite for the new objects in this pulse.
Mathematical representation
Mathematical representation separately records verbal rules, symbolic expressions, finite tables, ordered pairs and coordinate data for the same object, using explicit semantic bridges to check agreement.
Diagnostic mathematical assessment records
A diagnostic mathematical assessment record binds an item, its expected result, a response and an explicit judgment rule, producing only a traceable rule-agreement status.
Orbits, fixed points and periodic points
Repeated iteration of a self-map forms an orbit. Fixed points have period 1; the least positive period of a periodic point must be distinguished from an arbitrary return time.
Initial-value problem
An initial-value problem adds function or derivative values at a specified point to a differential equation; candidate checks are distinct from existence and uniqueness.
Finite sign-bracket updates in the bisection method
Using supplied endpoint and midpoint signs, bisection takes a midpoint and retains the opposite-sign half or a detected zero; finite nonterminal bisections halve the interval width.
Linear programming
Linear programming optimizes a linear objective over a feasible domain defined by linear equalities or inequalities; this exercise slice checks only a complete explicit finite candidate grid.
Discrete logistic increment model
For fixed capacity K and 0≤r≤1, this entry uses x_(n+1)=x_n+r*x_n*(1−x_n/K) to describe each capacity-limited discrete increment.
Path source & status
path-pulse-foundations-20261021 · candidate