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Author

Timo Hämäläinen

Other affiliations: Dalian Medical University, Nokia, Dublin Institute of Technology  ...read more
Bio: Timo Hämäläinen is an academic researcher from University of Jyväskylä. The author has contributed to research in topics: Quality of service & Encoder. The author has an hindex of 38, co-authored 560 publications receiving 7648 citations. Previous affiliations of Timo Hämäläinen include Dalian Medical University & Nokia.


Papers
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Book ChapterDOI
10 Sep 2007
TL;DR: The simulation results reveal that the ARQ mechanism plays an important role in transmitting data over wireless channels in the IEEE 802.16 networks.
Abstract: The IEEE 802.16 technology defines the ARQ mechanism that enables a connection to resend data at the MAC level if an error is detected. In this paper, we analyze the key features and parameters of the ARQ mechanism. In particular, we consider a choice for the ARQ feedback type, a scheduling of the ARQ feedbacks and retransmissions, the ARQ block rearrangement, ARQ transmission window and ARQ block size. We run a number of simulation scenarios to study these parameters and how they impact a performance of application protocols. The simulation results reveal that the ARQ mechanism plays an important role in transmitting data over wireless channels in the IEEE 802.16 networks.

20 citations

Proceedings ArticleDOI
30 Aug 2005
TL;DR: TTA processors for the RC4 and AES encryption algorithms of the new IEEE 802.11i WLAN security standard are designed and special operations efficiently supporting the ciphers are developed.
Abstract: Transport triggered architecture (TTA) offers a cost-effective trade-off between the size and performance of ASICs and the programmability of general-purpose processors. In this paper TTA processors for the RC4 and AES encryption algorithms of the new IEEE 802.11i WLAN security standard are designed. Special operations efficiently supporting the ciphers are developed. The TTA design flow is utilized for finding configurations with the best performance-size ratios. The size of the configuration supporting both the algorithms is 69.4 kgates and the throughput 100 Mb/s for RC4 and 68.5 Mb/s for AES at 100 MHz in the 0.13 /spl mu/m CMOS technology. Compared to commercial processors of the same wireless application domain, higher throughputs are achieved at significantly smaller area and lower clock speed, which also results in decreased energy consumption.

20 citations

Proceedings ArticleDOI
19 Aug 2016
TL;DR: This work shows that optimizing primarily these functions doubles the coding speed of a single-threaded Kvazaar intra encoder for the same rate-distortion performance, justifying that Kvazar is currently the leading open-source HEVC intra encoding in terms of real-time coding speed and efficiency.
Abstract: This paper presents efficient SIMD optimizations for the open-source Kvazaar HEVC intra encoder. The C implementation of Kvazaar is accelerated by Intel AVX2 instructions whose effect on Kvazaar ultrafast preset is profiled. According to our profiling results, C functions of SATD, DCT, quantization, and intra prediction account for over 60% of the total intra coding time of Kvazaar ultrafast preset. This work shows that optimizing primarily these functions doubles the coding speed of a single-threaded Kvazaar intra encoder for the same rate-distortion performance. The highest performance boost is obtained by deploying the proposed optimizations jointly with multithreading. On the Intel 8-core i7 processor, the AVX2-optimized 16-threaded Kvazaar ultrafast preset achieves real-time (30 fps) intra coding speed up to 1080p resolution. Compared to AVX2-optimized ultrafast preset of x265, Kvazaar is 20% times faster and still obtains 9.1% bit rate gain for the same quality. These results justify that Kvazaar is currently the leading open-source HEVC intra encoder in terms of real-time coding speed and efficiency.

20 citations

Proceedings ArticleDOI
26 Aug 2015
TL;DR: This paper presents the first reported HLS assisted implementation of HEVC encoder on SoC-FPGA, and obtained 9 fps full-HD intra prediction speed with a single accelerator on Altera Cyclone V SX on Terasic VEEK-MT-C5SoC board.
Abstract: This paper presents a High-Level Synthesis (HLS) flow for mapping a software HEVC encoder into Altera CycloneV SoC-FPGA. The starting point is a C implementation of an open-source Kvazaar HEVC intra encoder, which is minimally refined for SystemC design space exploration and automatic Catapult-C RTL generation. The final implementation involves Kvazaar encoder executed in Linux on dual-core ARM, and HW accelerated intra prediction on FPGA. Changing the SW/HW partitioning or modifying the implementation takes hours instead of weeks with Catapult-C HLS. In addition, the design is portable to other platforms without major manual re-writing. We obtained 9 fps full-HD intra prediction speed with a single accelerator on Altera Cyclone V SX on Terasic VEEK-MT-C5SoC board including video capture and HEVC video streaming via Ethernet. To the best of our knowledge, this is the first reported HLS assisted implementation of HEVC encoder on SoC-FPGA.

20 citations

Proceedings ArticleDOI
01 Jun 2020
TL;DR: An intelligent defense system implemented as a reinforcement machine learning agent that processes current network state and takes a set of necessary actions in form of software-defined networking flows to redirect certain network traffic to virtual appliances is proposed.
Abstract: With the recent progress in the development of low-budget sensors and machine-to-machine communication, the Internet-of-Things has attracted considerable attention. Unfortunately, many of today's smart devices are rushed to market with little consideration for basic security and privacy protection making them easy targets for various attacks. Unfortunately, organizations and network providers use mostly manual workflows to address malware-related incidents and therefore they are able to prevent neither attack damage nor potential attacks in the future. Thus, there is a need for a defense system that would not only detect an intrusion on time, but also would make the most optimal real-time crisis-action decision on how the network security policy should be modified in order to mitigate the threat. In this study, we are aiming to reach this goal relying on advanced technologies that have recently emerged in the area of cloud computing and network virtualization. We are proposing an intelligent defense system implemented as a reinforcement machine learning agent that processes current network state and takes a set of necessary actions in form of software-defined networking flows to redirect certain network traffic to virtual appliances. We also implement a proof-of-concept of the system and evaluate a couple of state-of-art reinforcement learning algorithms for mitigating three basic network attacks against a small realistic network environment.

20 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
01 Nov 2007
TL;DR: Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

4,123 citations

01 Jan 2006

3,012 citations

01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

2,933 citations