\documentclass{llncs}
\usepackage{psfig}
\usepackage{graphicx}

\begin{document}

\title{This is a Template of How to Put Two ps-Made 
Pictures into a \LaTeX-Made Text and How to Make the
References}

\author{Innokentiy Semushin}

\institute{Ulyanovsk State University,
42 Leo~Tolstoy Str., 432970 Ulyanovsk, Russia\\
\email{SemoushinIV@ulsu.ru $\quad$
http://staff.ulsu.ru/semoushin/} }

\maketitle

\begin{center}
\begin{tabular}{c}
\includegraphics[scale=0.55,angle=45]{D_1.PS}
\end{tabular}
\end{center}



{\bf Attention!} The proof that minimum of Auxiliary Performance Index is necessary and sufficient
condition for filter optimality has been published in English-language literatute 

\begin{center}
\includegraphics[scale=0.436,angle=135]{D_2.PS}
\end{center}


in \cite{Semoushin00}. However in Russian, it was published earlier in
\cite{Semoushin85} and \cite{Semoushin94}.


\begin{eqnarray}
\label{eq28}
\begin{array}{lclclclclcl}
A&=&\left[
\begin{array}{rcl}
0     &\hphantom{a} &1 \\
a_1 &\hphantom{a} &a_2
\end{array}\right],&\hphantom{aaa}&D&=&\left[
\begin{array}{r}
d_1     \\
d_2
\end{array}\right],&\hphantom{aaa}&\hat \theta^T&=&\left[
\begin{array}{lcccccr}
a_1 & \hphantom{a} & a_2 & \hphantom{a} & d_1 & \hphantom{a} & d_2
\end{array} \right] \enspace . \\
\end{array}
\end{eqnarray}


\begin{figure}
\setbox1=\vbox{
\hbox to \textwidth{\null\hfil
%\psfig{figure=D_1.ps,angle=0,width=0.48\textwidth}\hfil
\psfig{figure=Ris1.eps,angle=0,width=0.48\textwidth}\hfil
\psfig{figure=Ris2.eps,angle=0,width=0.48\textwidth}\hfil\null
} \vspace{1ex}
        }
\noindent \copy1
\caption{Tracking the SSKF  parameters $k_1$ and $k_2$ by $d_1$
 ({\em left})  and $d_2$ ({\em right})  of (\ref{eq28})}
\label{grafic4}
\end{figure}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\begin{thebibliography}{1}

\bibitem{BassNik93}
Basseville, M., Nikiforov, I.:  Detection of Abrupt Changes:
Theory and Applications. Prentice-Hall Inc., New York (1993)

\bibitem{Landau01}
Landau, I.D. (ed.):  Identification des Systemes.  Les Bases de
l'Identification des Systemes. Hermes, Paris (2001)

\bibitem{Caines88}
Caines, P.:  Linear Stochastic Systems.  John Willey \& Sons, New
York Chichester Brisbane Toronto Singapore (1988)

\bibitem{Soderstrom81}
Soderstrom, T.: Identification  of stochastic linear systems in
presence of input noise. Automatica {\bfseries 17} (1981) 713--725

\bibitem{Ansay99}
Ansay, P., Gevers, M., Wertz, V.:  Closed-loop or open-loop models
in identification for control? In: Proc. of the European Control
Conference (1999) CD-ROM F544

\bibitem{Semoushin85}
Semoushin, I.V.:  Adaptive  Identification and Fault Detection
Methods in Random Signal Processing.  Saratov University
Publishers, Saratov  (1985) [{\em in Russian}]

\bibitem{Semoushin94}
Semoushin, I.V.: Adaptive control for stochastic linear plants
under conditions of uncertainty.  Nonlinear Dynamical Systems -
Qualitative Analysis and Control: Collected Papers, The Institute
for System Analysis of the Russian Academy of Sciences {\bfseries
2}  (1994) 104--110

\bibitem{Semoushin00}
Semoushin, I.V., Tsyganova, J.V.: Indirect error control for
adaptive filtering.  In: Neittaanmaki, P., Tiihonen, T.,
Tarvainen, P. (eds.): Proc. of the 3rd  European Conference on
Numerical Mathematics and Advanced Applications. World Scientific,
Singapore New Jersey London Hong Kong (2000) 333--340

\bibitem{Semoushin02-2}
Semoushin, I., Gorokhov, O.:  Computational processes in iterative
control design. In:  Sloot, P.M.A., Kenneth Tan, C.J., Dongarra,
J.J., Hoekstra, A.G. (eds.): Computational Science -- ICCS~2002.
Lecture Notes in Computer Science, Vol. 2329. Springer-Verlag,
Berlin Heidelberg New York Barcelona Hong Kong London Milan Paris
Tokyo (2002) 186--195

\bibitem{Kond2001}
Kondratiev, A.E., Fatyanova, O.A.:  Start-stop algorithms for
adaptive filtering. In: Boulyarski, S.V. (ed.): Young Researchers'
Collected Papers of the Ulyanovsk State University. UlSU
Publishers, Ulyanovsk (2001) 6--7

\end{thebibliography}

\end{document}