Molekuláris bionika és infobionika szakok tananyagának komplex

lar bionics who are specializing in the fields of 

Bionic  Interfaces  and  Bio-nano  measurement 

devices.

Parts of the course material are included in the 

following books: 



A.  Molisch,  Wireless  communications, 

Wiley-IEEE Press, 2005. 



A.  Goldsmith,  Wireless  communica-

tions,  Cambridge  university  press, 

2005.



C.S.R. Murthy and B.S. Manoj, Ad Hoc 

wireless  networks:  architectures  and 

protocols,  Prentice  Hall  PTR  Upper 

Saddle River, NJ, USA, 2004.  



E.H.  Callaway,  Wireless  sensor  net-

works:  architectures  and  protocols, 

CRC press, 2004.



D. Gislason, Zigbee Wireless Network-

ing, Newnes, 2008. 



G.Z.  Yang  and  M.  Yacoub,  Body  sen-

sor  networks,  Springer-Verlag  New 

York Inc, 2006. 

The references listed above provide a wide 

range  of  basis  knowledge.  But  the  real  chal-

lenge of the course is to present a comprehen-

sive  foundation  which  addresses  all  the  engi-

neering  challenges  and  list  the  corresponding 

practical solutions. This must be done on such 

a mathematical platform which takes into ac-

count  only  those  skills  which  have  already 

been  obtained  in  the  studies  preceding  the 

course.  The  books  above  cannot  fulfill  these 

objectives by themselves.  

Dr. András Oláh can successfully guide the 

students  through  the  course.  Furthermore,  as 

his  research  area  is  wireless  communication, 

he  can  expose  the  students  to  the  newest  re-

sults of the field. 

One of the research areas of Prof. Dr. János 

Levendovszky is also wireless communication 

and  their  technological  challenges  (wireless 

detection,  channel  equalization,  energy  aware 

routing in wireless sensor networks). He lead 

several projects in the filed as principal inves-

tigator and supervised numerous PhD students 

as well.

As a result, the expertise and skills to pro-

vide a high level course in the field is availa-

ble.

III.

R

ESULTS

The course material has been split into 12 

parts, as follows:  

1. Overview of wireless communications 

2. Fundamentals  and  technical  challenges 

of wireless communications 

3. Wireless  channel  characterization  and 

models 

4. Digital modulation 

5. Detection and channel equalization 

6. Multiple channel access 

7. Routing protocols 

8. Standardized wireless systems 

9. Communication  protocols  for  wireless 

sensor networks 

10. Localization  algorithms  and  strategies 

for wireless sensor networks 

11. Applications of ad hoc and sensor net-

works 

12. Future  of  wireless  technology  and  re-

search

The  approximatively  500  slides  had  not 

been  uniformly  divided  and  dedicated  to  the 

12  chapters,  but  based  on  the  importance  of 

the topics. 

The first half of the material deals with the 

foundations of wireless communication which 

is then followed by the particular challenges of 

ad hoc and sensor networks from Chapter 8. 

It is important to note that during the course 

the students also choose a project the goals of 

which can then be completed on the infrastruc-

ture available at the WSN laboratory (software 

radio,  Texas  nodes,  Xbow  Mica2  mote-ok, 

Android  based  mobile  telephones,  Arduino 

devices).  In  this  way,  the  students  can  grow 

familiar  with  the  standard  devices  and  devel-

opment  kits  and  become  capable  of  R&D  in 

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the field of wireless communication technolo-

gies.

IV.

S

UMMARY

The  course  can  provide  comprehensive 

foundations  combined  with  up-to-the-minute

 technological details in the domain of wireless 

communication technologies to the students. It 

also provides the knowledge which is needed 

for  the  engineers  to  keep  track  of  the  ever 

changing and evolving technologies and appli-

cations.

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43

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An Integrated Approach to Linear- and 

Nonlinear Signal Processing 

Digital- and Neural Based Signal Processing & Kiloprocessor Arrays 

András Oláh, Dávid Tisza, Gergely Treplán, 

Kálmán Tornai 

Péter Pázmány Catholic University 

Faculty of Information Technology 

Budapest, Hungary 

[olah,tisda,trege,kami]@itk.ppke.hu 

János Levendovszky 

Budapest University of Technology and Economics 

Department of Telecommunications 

Péter Pázmány Catholic University 

Faculty of Information Technology 

Budapest, Hungary 

[e-mail]  

Summary— The course objective is to give a 

comprehensive introduction to digital signal 

processing using the traditional linear- and 

nonlinear approaches. This objective is very 

important as the material treated in this course 

forms the foundation of plenty other subjects. 

As a result, without a clear-cut and well-

presented course on signal processing, the stu-

dent may miss out on the understanding of 

further courses in the curriculum. Hence, the 

course must integrate the basic concepts of 

linear signal processing in the time- and trans-

formation domain together with the biological-

ly inspired computational paradigms imple-

mented by artificial neural networks and the 

signal processing algorithms running on kilo-

processor arrays. Besides delving into the theo-

retical foundations, the course tries to demon-

strate each principle by applications in the field 

of information technologies (e.g. adaptive algo-

rithms for channel equalization and data com-

pression, pattern recognition and data mining 

examples). In this way, the students can come 

to grip with basic notions of signal processing 

via applications as well. 

Keywords: digital signal processing, neural 

networks and computing 

I.

I

NTRODUCTION

The  two  fundamental  areas  of  signal  pro-

cessing are (i) linear; and (ii) nonlinear signal 

processing.  Treating  both  of  the  areas  in  one 

course has the advantage of addressing general 

issues such as (i) representation; (ii) learning; 

(iii)  and  generalization  together.  In  this  way, 

the  students  are  not  only  exposed  to  the  de-

scription  of  signals  in  time-  and  transform 

domains, but to the fundamental issues of sig-

nal processing as well. This helps to open up 

new  horizons  of  understanding  not  only  in 

linear but also neural based signal processing. 

This  can  serve  the  orientation  of  students  in 

the  info-bionics  program  who  need  to  get  an 

insight  into  the  signal  processing  paradigms 

emerging neural based systems. 

The third part of the course deals with kilo-

processor based signal processing which is an 

important direction of present day signal pro-

cessing  technologies.  These  technologies 

make possible to integrate 5 billion transistors 

in  a  single  chip,  which,  however  poses  new 

challenges  to  signal  processing  (taking  into 

account  dissipation  and  signal  propagation 

delays). Thus it is important to highlight how 

to  implement  the  traditional  algorithms  on 

these novel architectures. 

The  course  materials  (slides,  dictionary, 

etc.) have been designed to serve this integral 

approach to signal processing. 

II.

M

ATERIALS ALREADY AVAILABLE FOR 

THE COURSE

Some  of  the  topics  touched  upon  in  the 

course can be found in the following books: 



J.G. Proakis and D.G. Manolakis, Digi-

tal  Signal  Processing,  Prentice  Hall, 

1996;

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