Evolution of Biological Systems in Random Media: Limit Theorems and Stability (Mathematical Modelling: Theory and Applications, ,Used

Evolution of Biological Systems in Random Media: Limit Theorems and Stability (Mathematical Modelling: Theory and Applications, ,Used

In Stock
SKU: SONG1402015542
Brand: Springer
Condition: Used
Regular price$75.74
Quantity
Add to wishlist
Add to compare

Sold by Ergodebooks, an authorized reseller.

Returns accepted within 30 days | support@ergodebooks.com

Verified
Shipping Information
  • Free Standard Shipping — United States only
  • Processing Time: 1–3 business days
  • Estimated Delivery: 3–5 business days after dispatch
  • Double-boxed, fully insured & discreetly packaged
  • Tracking number sent via email once dispatched
  • Orders over $250 require signature upon delivery. Taxes calculated at checkout.
Returns & Refund

Returns accepted within 30 days of delivery.

Damaged or Defective Item

Free return shipping + replacement or full refund

Wrong Item Received

Free return shipping + replacement or full refund

Change of Mind

Return shipping at customer's expense · 25% restocking fee applies

All returns require a Return Authorization (RA) number before sending.

To initiate a return, contact us:

support@ergodebooks.com +1 (281) 738-1050
View Full Return & Refund Policy
Payment Option
Payment Methods

Help

If you have any questions, you are always welcome to contact us. We'll get back to you as soon as possible, withing 24 hours on weekdays.

Customer service

All questions about your order, return and delivery must be sent to our customer service team by e-mail at yourstore@yourdomain.com

Sale & Press

If you are interested in selling our products, need more information about our brand or wish to make a collaboration, please contact us at press@yourdomain.com

The book is devoted to the study of limit theorems and stability of evolving biologieal systems of "particles" in random environment. Here the term "particle" is used broadly to include moleculas in the infected individuals considered in epidemie models, species in logistie growth models, age classes of population in demographics models, to name a few. The evolution of these biological systems is usually described by difference or differential equations in a given space X of the following type and dxt/dt = g(Xt, y), here, the vector x describes the state of the considered system, 9 specifies how the system's states are evolved in time (discrete or continuous), and the parameter y describes the change ofthe environment. For example, in the discretetime logistic growth model or the continuoustime logistic growth model dNt/dt = r(y)Nt(lNt/K(y)), N or Nt is the population of the species at time n or t, r(y) is the per capita n birth rate, and K(y) is the carrying capacity of the environment, we naturally have X = R, X == Nn(X == Nt), g(x, y) = r(y)x(lxl K(y)), xE X. Note that n t for a predatorprey model and for some epidemie models, we will have that X = 2 3 R and X = R, respectively. In th case of logistic growth models, parameters r(y) and K(y) normaIly depend on some random variable y.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

Recently Viewed