Calculus for Cognitive Scientists

Part I. Introduction

1. Introductory Remarks
James K. Peterson

Part II. Using One Variable

2. Viability Selection
James K. Peterson

3. Limits and Basic Smoothness
James K. Peterson

4. Continuity and Derivatives
James K. Peterson

5. Sin, Cos and All That
James K. Peterson

6. Antiderivatives
James K. Peterson

7. Substitutions
James K. Peterson

8. Riemann Integration
James K. Peterson

9. The Logarithm and Its Inverse
James K. Peterson

10. Exponential and Logarithm Function Properties
James K. Peterson

11. Simple Rate Equations
James K. Peterson

12. Simple Protein Models
James K. Peterson

13. Logistics Models
James K. Peterson

14. Function Approximation
James K. Peterson

15. Extreme Values
James K. Peterson

16. Numerical Methods Order One ODEs
James K. Peterson

17. Advanced Protein Models
James K. Peterson

Part III. Using Multiple Variables

18. Matrices and Vectors
James K. Peterson

19. A Cancer Model
James K. Peterson

20. First Order Multivariable Calculus
James K. Peterson

21. Second Order Multivariable Calculus
James K. Peterson

22. Hamilton’s Rule in Evolutionary Biology
James K. Peterson

Part IV. Summing It All Up

23. Final Thoughts
James K. Peterson

Part V. Advise to the Beginner

24. Background Reading
James K. Peterson

Avainsanat: Engineering, Computational Intelligence, Mathematical Models of Cognitive Processes and Neural Networks, Theoretical, Mathematical and Computational Physics, Artificial Intelligence (incl. Robotics), Computer Imaging, Vision, Pattern Recognition and Graphics