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Hopf Bifurcation in a Modified Leslie-Gower Two Preys One Predator Model and Holling Type II Functional
Response with Harvesting and Time-Delay
Gesti Essa Waldhani
1*, Chalimatusadiah
2**Program Studi S1 Teknologi Informasi, FTI, Universitas Bina Sarana Informatika Email address: gesti.gew@bsi.ac.id1, chalimatusadiah.cld@bsi.ac.id2
Received:30 December 2022; Accepted: 23 March 2023; Published: 5 May 2023
Abstract
In this paper, a modified Leslie-Gower two preys one predator model and Holling type II functional response with harvesting and time-delay were discussed. Model analysis is carried out by determining fixed points, then analyzing the stability of the fixed points and discussing the existence of the Hopf bifurcation. In some conditions that occur in nature indicate the occurrence of hunting of prey and predator species by humans. Therefore, this model is modified by adding the assumption that prey and predators are being harvested. Another modification given to the model is the use of time delays.The delay time term is for taking into account the case that the members of the predator species need time from birth to predation for being active predators. The first case is a model without time delay, it is obtained that 3 fixed points are unstable and 7 fixed points are stable. One of them is the interior fixed point tested with the Routh-Hurwitz criteria. The second case is a model with a delay time, the critical delay value is obained. Hopf bifurcation occurs when the delay time value is equal to the critical delay value and also fulfills the transversality condition. Observations on the model simulation are carried out by varying the value of the delay time. When the Hopf bifurcation occurs, the graph on the solution plane shows a constant oscillatory movement. If the value of the delay time given is less than the critical value of the delay, the controlled system solution goes to a balanced state.
Then when the delay time value is greater than the critical delay value, the system solution continues to fluctuate causing an unstable system condition.
Keywords: Hopf bifurcation; Leslie-Gower; two preys; Holling type II; harvesting;
time delay.
1.
INTRODUCTION AND PRELIMINARIES
One example of system which is the approach to the physical phenomenon is the predator-prey system [1]. The research of the interaction of predator-prey will be done by analyzing the mathematical model of predator-prey system.
The predator-prey model were first introduced in 1925 by Lotka and Volterra in 1926 [2,3], so this model is also called the Lotka-Volterra model [4]. This simple model has been modified in many ways since its original formulation in the 1920s. In particular, Leslie and Gower [5, 6]
improved the realism of the Lotka-Volterra model by introducing the predator-prey model where environmental carrying capacity for the predator population is proportional to the number of prey population. Then in 1950 Holling introduced the functional response. The functional response in ecology i.e. the amount of food is eaten by the predator population as the function of the density of food [7]. In this case the functional response is divided into three kinds i.e. type I functional response, type II functional response and type III functional response. Then to build the model which is more realistic, Ali, et al [8] consider time delay. Delay effect here is to realize the situation that the predator population needs time from birth to predation. This means that a newborn predator species need time to grow old enough to predate alone and to be represented in the predation function mathematically.
The Leslie Gower predator-prey model and Holling type 2 functional response with time delay were introduced by Nindjin et al [9] after that Ma [10] added a time delay to the previous model with the assumption that the growth of the prey population depended on the previous population size. Aziz and Daher [11] studied global stability of the coexisting interior equilibrium in modified Leslie-Gower Predator-prey and Holling Type II Functional Response. Pan-Ping & Yong [12]
analyzed spatiotemporal dynamics of a predatorโprey model obtain rich patterns, including spotted, black-eye, and labyrinthine patterns with choosing appropriate parameter values. Tapan &
Charugopala [13] proposed a delayed HollingโTanner predatorโprey model with ratio-dependent functional response. The local stability, Hopf-bifurcation, qualitative behaviour of the singularity with blow up transformation and global stability are discussed. Zhiqing and Hongwei [14]
investigated the global stability of equilibrium of HollingโTanner model with ratio-dependence by constructing Lyapunov function and discuss the existence limit cycle of model linear. Malay and Santo [15] considered a modified spatiotemporal ecological system originating from the temporal HollingโTanner model with diffusion. The original ODE system is studied for the stability of coexisting homogeneous steady-states. The modified PDE system is investigated in detail with both numerical and analytical approaches. Turing and non-Turing patterns of fixed values and Hopf bifurcation are discussed. Zizhen Zhang [16] analyzed Hopf bifurcation analysis for a two prey one predator system with time delay and show the hybrid controller is efficient in controlling Hopf bifurcation. Xinzhi, et al [17] studied the existence of invasion waves of a diffusive predatorโprey model with two preys and one predator. The existence of traveling semi-fronts connecting invasion- free equilibrium is obtained by Schauderโs fixed-point theorem The existence of traveling front is got by rescaling method and limit arguments. Gakkhar, S and Kamel Naji, R [18] investigated the dynamical behavior and chaos of a realistic three species food chain model considering predator to prey ratio-dependence for the interaction together with type II functional response. The bifurcation diagrams, Lyapunov exponents and dimensions are discussed. Xiaoliang and Wen [19] concerned a three-species Lotka-Volterra food chain system with multiple delays. The direction and the stability of bifurcating periodic solutions are determined by the normal form theory and the center manifold theorem. Nilesh, et al [20] discussed modeling the planktonโfish. Interaction between the prey and an intermediate predator follows the MonodโHaldane functional response, while that between the top predator and its prey depends on BeddingtonโDeAngelis-type functional response.
we study the Hopf and transcritical bifurcations scenarios with respect to inhibitory effect of phytoplankton against zooplankton and death rate of fish population for the non-delayed system.
Jia-Fang [21] studied the direction of Hopf bifurcation and explicit algorithm is given by applying
the normal form theory and the center manifold reduction. Zhiqi and Xia [22] discussed a predatorโ
prey model with modified HollingโTanner functional response and time delay. The local stability and global stability with Lyapunov theorem is investigated.
The model discussed in this study is a modification of the model formulated by Ali, et al [8]
with the assumption that in some conditions that occur in nature indicate the occurrence of hunting by humans. To control the level of predation so as not to cause extinction of the prey and predator species, a constant harvesting treatment is given to the prey and predator populations on a regular basis. In general, harvesting activities are carried out on individuals who have reached a certain age which are considered mature or ripe for harvesting. According to Idels and Wong [23] constant harvesting does not increase or decrease every year. In this research, it is assumed that harvesting can produce results that do not cause the species to become extinct. Based on the author's literature review, this modified model has never been studied before. Model analysis is carried out by determining the fixed point, then a stability analysis is performed from the fixed point without time delay including interior points tested with Routh Hurwitz criteria and time delay interior fixed points by applying Hopf bifurcation theory which is continued with model simulations carried out by varying the value of delay time.
2. METHOD
The stages of the research carried out are as follows.
1. Journal Review
In general, the content of the article is about the analysis of the stability of the Leslie Gower equation and the Holling type II response function with harvesting and delay time.
2. Model Building
The modified Leslie Gower model and the Holling type II response function which will be studied in this study were obtained from the development of previous research models.
3. Fixed Point determination stage
The fixed point is obtained by making the rate of change of predator and prey with respect to time equal to zero.
4. Fixed Point Stability Analysis Stage
Fixed point stability without time delay is obtained by a linear approach. The interior points are substituted into the Jacobi matrix so that the eigenvalues can be analyzed with Routh Hurwitz to determine stability. A fixed point with a time delay requires an approach in complex space to analyze the Hopf bifurcation.
5. Stage of Determination of Transverse Conditions
The transverse condition is determined to prove that a Hopf bifurcation occurs at the inner equilibrium point.
6. Interior Point Stability Simulation Stage
Simulations are carried out for each parameter according to the conditions. The simulation results were analyzed, in order to obtain an overview of the influence of harvesting and delay time on predators and prey.
3. MATHEMATICAL MODEL
A modified Leslie-Gower two preys one predator model and Holling type II functional response and harvesting consists of two different prey density at time ๐ก (๐ฅ1(๐ก) ๐๐๐ ๐ฅ2(๐ก)) and the predator population at time ๐ก (๐ฅ3(๐ก)).
The prey population density depends on several factors, including the growth rate of each prey and predator population, carrying capacity for the prey population, the maximum consumption rate of the predator population and the saturation rate of the predation.
The predator population density depends on several factors, including the growth rate of the predator population, the maximum consumption rate of the predator population and the saturation rate of the predation.
In the formation of this model, there are several assumptions. The assumptions is used in the modified Leslie-Gower two preys one predator model and Holling type II functional response and harvesting are (1) The predator can eat both preys, meantime there is no interaction between ๐ฅ1 and ๐ฅ2 (2) The growth rate of the prey population has a logistic growth pattern. (3) In the interaction between prey and predator, the prey responds the presence of the predator, such that the predator takes time to catch the prey (predator following the Holling type II functional response). (4) There is the harvesting in the prey and predator population after the prey and predator population density reaches a threshold harvesting. A modified Leslie-Gower two preys one predator model and Holling type II functional response and harvesting can be expressed as.
(1) ๐๐ฅ1
๐๐ก = ๐1๐ฅ1(1 โ๐ฅ1
๐พ1) โ๐1๐ฅ1๐ฅ3
๐1+๐ฅ1 โ ๐1๐น๐ฅ1, (2) ๐๐ฅ2
๐๐ก = ๐2๐ฅ2(1 โ๐ฅ2
๐พ2) โ๐2๐ฅ2๐ฅ3
๐2+๐ฅ2 โ ๐2๐น๐ฅ2, (3) ๐๐ฅ3
๐๐ก = ๐ 1๐ฅ3(1 โ๐1๐ฅ3
๐พ1 ) + ๐ 2๐ฅ3(1 โ๐2๐ฅ3
๐พ2 ) โ ๐ 1๐น๐ฅ3โ ๐ 2๐น๐ฅ3. (1) with ๐ฅ1(0) > 0, ๐ฅ2(0) > 0 and ๐ฅ3(0) > 0.
๐ฅ1 = ๐พ1๐ฅ, ๐ฅ2= ๐พ2๐ฆ, ๐1๐ฅ3= ๐พ1๐ง โบ ๐ฅ3=๐พ1๐ง
๐1 , ๐2๐ฅ3= ๐พ2๐ง โบ ๐ฅ3 =๐พ2๐ง
๐2 , ๐1๐ก = ๐ โบ ๐ก =
๐
๐1, ๐2๐ก = ๐ โบ ๐ก = ๐
๐2 ๐ผ1= 1
๐1, ๐ผ2= 1
๐2 ๐ฝ1= ๐1
๐1, ๐ฝ2=๐2
๐2 ๐1 =๐1
๐พ1โบ ๐1 = ๐1๐พ1, ๐2=๐2
๐พ2โบ ๐2= ๐2๐พ2, ๐1=๐ 1
๐1โบ ๐ 1= ๐1๐1, ๐2=๐ 2
๐2 โบ ๐ 2= ๐2๐2. In the equation system (1), the parameter ๐ฅ =๐ฅ1
๐พ1 and ๐ฆ =๐ฅ2
๐พ2 describes that the prey population density with the influence of the surroundings, the parameter ๐ง =๐1๐พ๐ฅ3
1 =๐๐พ2๐ฅ3
2 shows that the predator population density with the influence of the surroundings which is interacting with the prey population, ๐ = ๐1๐ก = ๐2๐ก shows the time ๐ก, ๐ผ1= 1
๐1 and ๐ผ2= 1
๐2 describes that the decrease number of the prey population that caused the interaction of the prey and predator population, ๐ฝ1=๐1
๐1, ๐ฝ2=๐2
๐2 shows that the decrease number of the predator population that caused the interaction between one predator and the other predator population, ๐1=๐1
๐พ1, ๐2=๐2
๐พ2 describes that the saturation rate of the predation with the influence of the surroundings and ๐1=๐ 1
๐1, ๐2=๐ 2
๐2 describes that the growth rate of the predator population. So, system (1) is equivalent with the following system.
(1) ๐๐ฅ
๐๐= ๐ฅ (1 โ ๐ฅ โ ๐ผ1๐ง
๐1+๐ฅโ ๐น), (2) ๐๐ฆ
๐๐= ๐ฆ (1 โ ๐ฆ โ๐๐ผ2๐ง
2+๐ฆโ ๐น), (3) ๐๐ง
๐๐= ๐ง(๐1(1 โ ๐ฝ1๐ง) + ๐2(1 โ ๐ฝ2๐ง) โ ๐น) (2)
with ๐ฅ(0) > 0, ๐ฆ(0) > 0 and ๐ง(0) > 0.
Then by giving the discrete time-delay in the growth rate of the predator population, the equation models become
(1) ๐๐ฅ(๐)
๐๐ = ๐ฅ(๐) (1 โ ๐ฅ(๐) โ ๐ผ1๐ง(๐โ๐)
๐1+๐ฅ(๐โ๐)โ ๐น)
(2) ๐๐ฆ(๐)
๐๐ = ๐ฆ(๐) (1 โ ๐ฆ(๐) โ ๐ผ2๐ง(๐โ๐)
๐2+๐ฆ(๐โ๐)โ ๐น) (3) ๐๐ง(๐)
๐๐ = ๐ง(๐)(๐1(1 โ ๐ฝ1๐ง(๐ โ ๐)) + ๐2(1 โ ๐ฝ2๐ง(๐ โ ๐)) โ ๐น) (3)
with ๐ฅ(0) > 0, ๐ฆ(0) > 0 and ๐ง(0) > 0.
4. MAIN RESULTS
4.1 EQUILIBRIA
System (3) realizes the equilibrium point when ๐๐ฅ
๐๐= 0, ๐๐ฆ
๐๐= 0 and ๐๐ง
๐๐= 0, such that system (3) can be written as.
(a) ๐๐ฅ
๐๐= ๐ฅ (1 โ ๐ฅ โ ๐ผ1๐ง
๐1+๐ฅโ ๐น) = 0, (b) ๐๐ฆ
๐๐= ๐ฆ (1 โ ๐ฆ โ ๐ผ2๐ง
๐2+๐ฆโ ๐น) = 0, (c) ๐๐ง
๐๐= ๐ง(๐1(1 โ ๐ฝ1๐ง) + ๐2(1 โ ๐ฝ2๐ง) โ ๐น) = 0 (4) From the equation c in system (4) we obtain ๐ง = 0 or ๐ง = ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2 with ๐1+ ๐2> ๐น.
For the case ๐ง = 0, substituting ๐ง = 0 into the equation (a) and (b) in system (4), such that we get ๐ฆ = 0 โจ ๐ฆ = 1 and ๐ฅ = 0 โจ ๐ฅ = 1. Hence, we obtain the equilibrium point ๐ธ0(0,0,0), ๐ธ1(0,1,0), ๐ธ2(1,0,1), ๐ธ3(1,1,0). For the case ๐ง = ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2, substituting ๐ง = ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2
into the equation (a) and (b) in system (4), then we obtain ๐ฅ = 0 โจ ๐ฅ = โ1
2(๐น โ 1 + ๐1ยฑ ๐ด) and ๐ฆ = 0 โจ ๐ฆ = โ1
2(๐น โ 1 + ๐1ยฑ ๐ต) with ๐ด = โ(๐นโ(๐1+1))
2(๐1๐ฝ1+๐2๐ฝ2)โ4๐ผ1(๐1+๐2โ๐น)
๐1๐ฝ1+๐2๐ฝ2 and ๐ต =
โ(๐นโ(๐2+1))2(๐1๐ฝ1+๐2๐ฝ2)โ4๐ผ2(๐1+๐2โ๐น)
๐1๐ฝ1+๐2๐ฝ2 where ๐น โ 1 + ๐1ยฑ ๐ด < 0 and ๐น โ 1 + ๐1ยฑ ๐ต < 0. So we have the equilibrium point ๐ธ4(0,0, ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2) , ๐ธ5(โ1
2(๐น โ 1 + ๐1+ ๐ด), 0, ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2) , ๐ธ6(0, โ1
2(๐น โ 1 + ๐1+ ๐ต), ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2) , ๐ธ7(โ1
2(๐น โ 1 + ๐1+ ๐ด), โ1
2(๐น โ 1 + ๐1+ ๐ต), ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2) , ๐ธ8(โ1
2(๐น โ 1 + ๐1โ ๐ด), 0, ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2) , ๐ธ9(0, โ1
2(๐น โ 1 + ๐1โ ๐ต),๐๐1+๐2โ๐น
1๐ฝ1+๐2๐ฝ2) , ๐ธ10(โ12(๐น โ 1 + ๐1โ ๐ด), โ12(๐น โ 1 + ๐1โ ๐ต),๐๐1+๐2โ๐น
1๐ฝ1+๐2๐ฝ2).
4.2 STABILITY OF ๐ฌ
ฬWITHOUT TIME DELAY
The general Jacobian matrix of Eqs. (4) is given by
๐ฝ = (
1 โ 2๐ฅ โ ๐ผ1๐ง
๐1+๐ฅ+ ๐ผ1๐ฅ๐ง
(๐1+๐ฅ)2โ ๐น 0 โ๐ผ1๐ฅ
๐1+๐ฅ
0 1 โ 2๐ฆ โ ๐ผ2๐ง
๐2+๐ฆ+(๐๐ผ2๐ฆ๐ง
2+๐ฆ)2โ ๐น โ๐ผ2๐ฆ
๐2+๐ฆ
0 0 ๐1(1 โ ๐ฝ1๐ง) โ ๐1๐ง๐ฝ1+ ๐2(1 โ ๐ฝ2๐ง) โ ๐2๐ง๐ฝ2โ ๐น )
At ๐ธ0, the Jacobian matrix is ๐ฝ(0,0,0) = (
1 โ ๐น 0 0
0 1 โ ๐น 0
0 0 ๐1+ ๐2โ ๐น
). We get ๐1,2= 1 โ ๐น โจ ๐3 = ๐1+ ๐2โ ๐น. Because 1 > ๐น and ๐1+ ๐2> ๐น, E0 is an unstable saddle point.
At ๐ธ1, the Jacobian matrix is ๐ฝ(0,1,0) = (
1 โ ๐น 0 0
0 โ1 โ ๐น โ ๐ผ2
๐2+1
0 0 ๐1+ ๐2โ ๐น
). We get ๐1,2= 1 โ ๐น โจ ๐3= ๐1+ ๐2โ ๐น. Hence, ๐ธ1 is an unstable saddle point.
At ๐ธ2, the Jacobian matrix is ๐ฝ(1,0,1) =
(
โ(๐1+1)(๐2(๐น+1)+๐ผ1๐1
1+1)2 0 โ ๐ผ1
๐1+1
0 โ๐2(๐นโ1)+๐ผ2
๐2 0
0 0 ๐1+ ๐2โ ๐น โ 2(๐1๐ฝ1+ ๐2๐ฝ2))
. We get ๐1=
โ(๐1+1)
2(๐น+1)+๐ผ1๐1
(๐1+1)2 โจ ๐2= โ๐2(๐นโ1)+๐ผ๐ 2
2 โจ ๐3= ๐1+ ๐2โ ๐น โ 2(๐1๐ฝ1+ ๐2๐ฝ2). E2 stable if ๐2(๐น โ 1) + ๐ผ2> 0 and ๐1+ ๐2โ ๐น < 2(๐1๐ฝ1+ ๐2๐ฝ2).
At ๐ธ3, the Jacobian matrix is ๐ฝ(1,1,0) = (
โ1 โ ๐น 0 โ๐๐ผ1
1+1
0 โ1 โ ๐น โ ๐ผ2
๐2+1
0 0 ๐1+ ๐2โ ๐น
). We get ๐1,2 = 1 โ ๐น โจ ๐3= ๐1+ ๐2โ ๐น. Hence, ๐ธ3 is an unstable saddle point.
At E4, the Jacobian matrix is ๐ฝ(1,1,0) =
(
โ๐1๐ฝ1๐1(โ1+๐น)+๐2๐ฝ2๐1(โ1+๐น)+๐ผ1(๐1+๐2โ๐น)
(๐1๐ฝ1+๐2๐ฝ2)๐1 0 0
0 โ๐1๐ฝ1๐2(โ1+๐น)+๐(๐2๐ฝ2๐2(โ1+๐น)+๐ผ2(๐1+๐2โ๐น)
1๐ฝ1+๐2๐ฝ2)๐2 0
0 0 โ๐1โ ๐2+ ๐น)
. We get ๐1= โ๐1๐ฝ1๐1(โ1+๐น)+๐(๐2๐ฝ2๐1(โ1+๐น)+๐ผ1(๐1+๐2โ๐น)
1๐ฝ1+๐2๐ฝ2)๐1 โจ ๐2 =
โ๐1๐ฝ1๐2(โ1+๐น)+๐2๐ฝ2๐2(โ1+๐น)+๐ผ2(๐1+๐2โ๐น)
(๐1๐ฝ1+๐2๐ฝ2)๐2 โจ ๐3= โ๐1โ ๐2+ ๐น. Hence, ๐ธ4 stable if ๐1๐ฝ1๐1(โ1 + ๐น) + ๐2๐ฝ2๐1(โ1 + ๐น) + ๐ผ1(๐1+ ๐2โ ๐น) > 0 and ๐1๐ฝ1๐2(โ1 + ๐น) + ๐2๐ฝ2๐2(โ1 + ๐น) + ๐ผ2(๐1+ ๐2โ ๐น) > 0.
At ๐ธ5, the Jacobian matrix is ๐ฝ (โ1
2(๐น โ 1 + ๐1+ ๐ด), 0, ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2) =
(
(๐ด+๐ผ1)(โ๐1+๐นโ1+๐ด)2(๐1๐ฝ1+๐2๐ฝ2)+4๐ผ1๐1(โ๐1โ๐2+๐น)
(๐1๐ฝ1+๐2๐ฝ2)(โ๐1+๐นโ1+๐ด)2 0 โ๐ผ1(๐นโ1+๐1+๐ด)
โ๐1+๐นโ1+๐ด
0 โ๐ผ2(๐1+๐2โ๐น)+๐2(๐นโ1)(๐1๐ฝ1+๐2๐ฝ2)
(๐1๐ฝ1+๐2๐ฝ2)๐2 0
0 0 โ๐1โ ๐2+ ๐น )
.
We get ๐1=(๐ด+๐ผ1)(โ๐1+๐นโ1+๐ด)2(๐1๐ฝ1+๐2๐ฝ2)+4๐ผ1๐1(โ๐1โ๐2+๐น)
(๐1๐ฝ1+๐2๐ฝ2)(โ๐1+๐นโ1+๐ด)2 โจ ๐2=
โ๐ผ2(๐1+๐2โ๐น)+๐(๐ 2(๐นโ1)(๐1๐ฝ1+๐2๐ฝ2)
1๐ฝ1+๐2๐ฝ2)๐2 โจ ๐3= โ๐1โ ๐2+ ๐น. Hence, ๐ธ5 stable if (๐ด +
๐ผ1)(โ๐1+ ๐น โ 1 + ๐ด)2(๐1๐ฝ1+ ๐2๐ฝ2) + 4๐ผ1๐1(โ๐1โ ๐2+ ๐น) < 0 dan ๐ผ2(๐1+ ๐2โ ๐น) + ๐2(๐น โ 1)(๐1๐ฝ1+ ๐2๐ฝ2) > 0.
At ๐ธ6, the Jacobian matrix is ๐ฝ (0, โ1
2(๐น โ 1 + ๐1+ ๐ต), ๐1+๐2โ๐น
๐1๐ฝ1+๐2๐ฝ2) =
(
โ๐ผ1(๐1+๐2โ๐น)+๐1(๐นโ1)(๐1๐ฝ1+๐2๐ฝ2)
(๐1๐ฝ1+๐2๐ฝ2)๐1 0 0
0 (๐ต+๐1)(โ2๐2(๐+๐นโ1+๐1+๐ต)2(๐1๐ฝ1+๐2๐ฝ2)+4๐ผ2๐2(๐นโ๐2โ๐1)
1๐ฝ1+๐2๐ฝ2)(โ2๐2+๐นโ1+๐1+๐ต)2 โโ2๐๐ผ2(๐นโ1+๐1+๐ต)
2+๐นโ1+๐1+๐ต
0 0 โ๐1โ ๐2+ ๐น )
. We get ๐1= โ๐ผ1(๐1+๐2โ๐น)+๐(๐ 1(๐นโ1)(๐1๐ฝ1+๐2๐ฝ2)
1๐ฝ1+๐2๐ฝ2)๐1 โจ ๐2=
(๐ต+๐1)(โ2๐2+๐นโ1+๐1+๐ต)2(๐1๐ฝ1+๐2๐ฝ2)+4๐ผ2๐2(๐นโ๐2โ๐1)
(๐1๐ฝ1+๐2๐ฝ2)(โ2๐2+๐นโ1+๐1+๐ต)2 โจ ๐3= โ ๐ผ2(๐นโ1+๐1+๐ต)
โ2๐2+๐นโ1+๐1+๐ต. Hence, ๐ธ6