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diff --git a/Introduction_To_Linear_Algebra_by_Gilbert_Strang/CH6/EX6.1.4/Ex6.1_4.r b/Introduction_To_Linear_Algebra_by_Gilbert_Strang/CH6/EX6.1.4/Ex6.1_4.r
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+# Packages used  : pracma
+# To install pracma,type following in command line while connected to internet
+# install.packages("pracma") 
+# package can be included by command " library(pracma) "
+# for more information about pracma visit https://cran.r-project.org/web/packages/pracma/index.html
+
+# Example : 4   Chapter : 6.1     Page No: 287
+# Eigen values and eigen vectors of Singualar matrix
+
+library(pracma)
+nullspacebasis <- function(A){
+  R<-rref(A)
+  m<-nrow(A)
+  n<-ncol(A)
+  pivotcol<-c() #vector to store the column numbers of pivot columns
+  freecol<-c()  #vector to store the column numbers of free columns
+  i<-1
+  j<-1
+  
+  # to find which columns are pivot and which are free
+  while(i<=m & j<=n){
+    if(R[i,j]==1){
+      pivotcol<-c(pivotcol,j)
+      i<-i+1
+      j<-j+1
+    }
+    else{
+      j<-j+1
+    }
+  }
+  y<-length(pivotcol)
+  freecol<-c(1:n)
+  freecol<-freecol[!freecol%in%pivotcol]
+  x<-length(freecol)
+  N<-c()
+  #find the basis for null space based on Row reduced echelon form of given matrix
+  if(y==n){
+    return(N)
+  }
+  for(i in 1:x){
+    temp<-c(1:n)
+    for(j in 1:x){
+      temp[freecol[j]]<-0
+    }
+    temp[freecol[i]]<-1
+    temp[freecol[i]]
+    for(j in 1:y){
+      temp[pivotcol[j]]<-R[j,freecol[i]]*-1
+    }
+    N<-c(N,temp)
+  }
+  N<-matrix(N,nrow=n,ncol=x)
+  #Basis for the nullspace of given matrix
+  return(N)
+}
+A<-matrix(c(1,2,2,4),ncol=2)
+sol<-eigen(A)
+print(sol)
+lambda<-sol$values
+print("The eigen values of the matrix are")
+print(lambda)
+I<-matrix(c(1,0,0,1),ncol=2)
+E1<-A-lambda[1]*I
+E1
+rref(E1)
+x1<-nullspacebasis(E1)
+E2<-A-lambda[2]*I
+rref(E2)
+x2<-nullspacebasis(E2)
+print("The eigen vectors of the matrix in normalized form are")
+print(x1)
+print(x2)
+#to get eigen vectors in the textbook multiply normalised vectors by scalars
+x1<-2*x1
+x2<--1*x2
+print("The eigen vectors of the matrix are ")
+print(x2)
+print(x1)
+#The  answer may slightly vary due to  rounding off values
+#The answers provided in the text book may vary because of the computation process
+#Both answers are correct , here it is taken -Ax+b=0 , In the text book it is considered as Ax-b=0