%\lr                                                          
\SecSlide{Introduction}
\begin{rawslide}
\begin{block} 	
We consider the system of linear equations
\begin{equation}\label{mainsystem}
\mathbf{A} \mathbf{u}= \mathbf{b},
\end{equation}
where $\mathbf{A}\in \mathbb{C}^{n \times n}$ and  $\mathbf{b}\in \mathbb{C}^{n\times n}$.
Assume that the matrix $\mathbf{A}$  has a splitting of the following form
\begin{align}
\label{orgsplit}
\mathbf{A}=  \hat{\mathcal P} + \mathcal S, ~~\hat{\mathcal P}  \in \mathbb{C}^{n\times n} ~\text{ is PSD   and}~  \mathcal S \in \mathbb{C}^{n\times n} ~\text{is skew-Hermitian. }
\end{align}
This means that the matrix $\mathbf{A}$ is of a positive semidefinite and skew-Hermitian splitting.
Let the matrix $\Sigma\in \mathbb{C}^{n \times n}$ be HPD \cite{bai192012}. 
\end{block}
\end{rawslide} 
\SecSlide{The EPSS Iteration}
\begin{plainslide}
	\begin{block} 	
	Consider the  generalized saddle point problems  of  the form
	\begin{equation}
	\label{saddle} 
	\mathcal{A}u\equiv \begin{bmatrix}
	A&B^*&\\-B&C
	\end{bmatrix} 
	 \begin{bmatrix}
	 x\\y
	 \end{bmatrix}=\begin{bmatrix}
	f\\g
	\end{bmatrix}\equiv b,
	\end{equation}
	where $A \in \mathbb{C}^{n\times n}$ and $C \in \mathbb{C}^{m\times m}$ are nonsymmetric  positive semidefinite, $ B \in  \mathbb{C}^{m \times n} $   $(m\leqslant n)$,   $f \in \mathbb {C}^n$ and $g \in \mathbb{C}^m$.
	\end{block}
\end{plainslide} 
\begin{rawslide}
	\begin{definitionblock}{Convernce and Semi Convergence}
		Let 
		$\mathbf{A}$ ...
	\end{definitionblock} \pause 
	\begin{theoremblock}{Theorem}
 Iterative method ... 
 		$\rho(\mathbf T)<1$ 
	 where
		\begin{align}\rho(\mathbf T)=\max\left\{ |\lambda|, ~ \lambda \in \sigma(\mathbf T) \right\},
			\end{align}
	\end{theoremblock}
\end{rawslide}
\SecSlide { EPSS Iterative Method} 
\begin{rawslide}
	\begin{exampleblock}{EPSS Iterative method}  
		$\mathbf{A}$ be a PD matrix 
		($\mathbf x^*(\mathbf{A}+\mathbf{A^*})\mathbf x \geq 0, \mathbf x\in \mathbb{C}^n$) and ...    
	\end{exampleblock}
 
	
	\begin{noteblock}{Note}
		In  
		،BTSS
		،TSS 
		،PSS   
		HSS 
		and
		SS ...  
	\end{noteblock}
\end{rawslide}
\begin{rawslide}
	\begin{theoremblock}{Eigenvalues of ... }  
		
		Let ...
	\end{theoremblock}  \pause

	
	\begin{corollaryblock}{      {EPSS} method} 
		If matrix 
		$\mathbf{A}$ ...
	\end{corollaryblock}
\end{rawslide} 
\begin{rawslide}
	\begin{exampleblock}{Example} 
 Consider
		\[
		\mathbf{A}=\begin{bmatrix}
		0&-1\\
		1&0
		\end{bmatrix} 
		\]  and 
		$\Sigma=I$   و $\mathbf{P}=\mathbf{A}$...  
	\end{exampleblock}
\end{rawslide}
 
\begin{rawslide}
	\begin{exampleblock}{All Splittings}
		\begin{enumerate}
			\item ${\mathbf P}_1=\mathbf D+\mathbf L+\mathbf U^*$. 
			\item ${\mathbf P}_2=\mathbf {B_D}+\mathbf {B_L}+\mathbf {B_U}^*$.
			\item ${\mathbf P}_3=\mathbf H_{\mathbf A}=\frac{1}{2}(\mathbf A+\mathbf A^*)$. 
			\item ${\mathbf P}_4={\mathbf A}$.  
		\end{enumerate}  
	\end{exampleblock}
\end{rawslide}
 
\begin{plainslide}
	\begin{block}
		\begin{enumerate}
			\item			Let 	$x= [1, 1, . . . , 1]^T$.
			\item  Use  (20) $GMRES$(20).
			\item ...
		\end{enumerate}
	\end{block}
\end{plainslide}


\begin{rawslide}
	\begin{table}[!htp]
		%	sidewaystable
		\begin{center}
			\textbf{\caption{\small  Itertion and CPU timing for   \textcolor{blue}{
					 $EPSS$ EPSS Iterative method}.}}
			\label{TblIEPS}
			\scalebox{.73}
			{ 
					\begin{tabu}{|c|c|||c|c|c|c|||c|c|c|c|||c|c|c|c|}\taburowcolors 2{blue!10 .. white!10} 
						\hline 
						%	&
						&$\Sigma=\alpha \mathbf Q_j$&\multicolumn{4}{c|}{$\mathbf {Q_1=I}$}&\multicolumn{4}{c|}{$ \mathbf {Q_2=D}$}&\multicolumn{4}{c|}{$\mathbf {Q_3=BD}$}\\ 
						\hline	
						% &
						$n$&$ \mathbf {  P}_ i$&$\mathbf {  P}_ 1(TSS)$&$\mathbf {  P}_ 2(BTSS)$&$\mathbf {  P}_ 3(HSS)$&$ \mathbf {  P}_ 4(SS)$&$\mathbf {  P}_ 1$&$\mathbf {  P}_ 2$&$\mathbf {  P}_ 3$&$\mathbf {  P}_ 4$&$\mathbf {  P}_ 1$&$\mathbf {  P}_ 2$&$\mathbf {  P}_ 3$&$\mathbf {  P}_ 4$\\ 
						\hline 
						%	\multirow[c]{10}{*}{\rotatebox{90}{‏\large\bfseries {\rl{پیش‌شرط‌‌ساز}}}}&  
						%	\multirow[c]{2}{*}
						{\bfseries 400}
						&CPU&0.22&0.07&0.07&0.05&0.06&0.03&0.04&0.04&0.04&0.04&0.02&0.05\\ 
						%	&
						&IT&40&39&37&77&7&9&7&8&6&8&4&5 \\   \cline{1-14} 
						%	&\multirow[c]{2}{*}
						{\bfseries 800}
						&CPU&0.11&0.06&0.08&0.08&0.07&0.04&0.06&0.06&0.08&0.06&0.04&0.14\\
						%    &
						&IT&58&55&40&99&8&9&7&8&7&8&4&5 \\    \cline{1-14} 
						%	&\multirow[c]{2}{*}
						{\bfseries 1600}
						&CPU&0.22&0.08&0.12&0.11&0.09&0.07&0.10&0.09&0.13&0.08&0.09&0.35\\ 
						%	&
						&IT&80&59&57&143&8&9&7&7&7&8&5&5 \\   \cline{1-14} 
						%	&\multirow[c]{2}{*}
						{\bfseries 3200}
						&CPU&1.33&0.40&0.51&0.34&0.33&0.31&0.47&0.37&0.50&0.38&0.49&1.26\\
						%	&
						&IT&94&70&73&205&9&10&7&7&8&11&5&5 \\    \cline{1-14} 
						%	&\multirow[c]{2}{*}
						{\bfseries 6400}
						&CPU&3.72&0.41&0.93&0.70&1.55&1.37&0.98&0.72&1.21&0.97&2.01&4.29\\   
						%	&
						&IT&129&73&73&280&8&12&7&6&10&13&5&5 \\   \hline
					\end{tabu}
		 }
		\end{center}
	\end{table}
\end{rawslide}
\newpage

\begin{rawslide}  
	\begin{algorithmblock}{Algorithm}
		\begin{enumerate}
				\item 
			Solve $As_1=x_1$.
			\item
		Let
			$s_2=Bs_1+x_2$. 	 
			\item  
			Solve $(\alpha I +BB^T)y_2= s_2$.
			\item
			Let 		$y_1=s_1-B^Ty_2$.
		\end{enumerate}
	\end{algorithmblock}
\end{rawslide} 

\newpage
\begin{block}
	{Block}
\end{block}
\pause
\begin{rawslide}
\begin{theoremblock}{Theorem}
\end{theoremblock}
\pause
\begin{lemmablock}{Lemma}
\end{lemmablock}
\pause
\begin{remarkblock}{Remark}
\end{remarkblock}
\pause
\begin{propositionblock}{Proposition}
\end{propositionblock}
\pause
\begin{noteblock}{Note}
\end{noteblock}
\pause
\begin{algorithmblock}{Algorithm}
\end{algorithmblock}
\pause
\begin{corollaryblock}{Corollary}
\end{corollaryblock}
\pause
\begin{definitionblock}{Definition}
\end{definitionblock}
\pause
\begin{proofblock}{Proof}
\end{proofblock}
\end{rawslide}
\SecSlide{References}
%\begin{block}
 
\scriptsize
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\bibliography{MyReferences}