A Generalization of Girod's Bidirectional Decoding Method to Codes with a Finite Deciphering Delay

Girod's encoding method has been introduced in order to efficiently decode from both directions messages encoded by using finite prefix codes. In the present paper, we generalize this method to finite codes with a finite deciphering delay. In particular, we show that our decoding algorithm can be realized by a deterministic finite transducer. We also investigate some properties of the underlying unlabeled graph

The Roles of Language Models and Hierarchical Models in Neural Sequence-to-Sequence Prediction

With the advent of deep learning, research in many areas of machine learning is converging towards the same set of methods and models. For example, long short-term memory networks are not only popular for various tasks in natural language processing (NLP) such as speech recognition, machine translation, handwriting recognition, syntactic parsing, etc., but they are also applicable to seemingly unrelated fields such as robot control, time series prediction, and bioinformatics. Recent advances in contextual word embeddings like BERT boast with achieving state-of-the-art results on 11 NLP tasks with the same model. Before deep learning, a speech recognizer and a syntactic parser used to have little in common as systems were much more tailored towards the task at hand. At the core of this development is the tendency to view each task as yet another data mapping problem, neglecting the particular characteristics and (soft) requirements tasks often have in practice. This often goes along with a sharp break of deep learning methods with previous research in the specific area. This work can be understood as an antithesis to this paradigm. We show how traditional symbolic statistical machine translation models can still improve neural machine translation (NMT) while reducing the risk for common pathologies of NMT such as hallucinations and neologisms. Other external symbolic models such as spell checkers and morphology databases help neural grammatical error correction. We also focus on language models that often do not play a role in vanilla end-to-end approaches and apply them in different ways to word reordering, grammatical error correction, low-resource NMT, and document-level NMT. Finally, we demonstrate the benefit of hierarchical models in sequence-to-sequence prediction. Hand-engineered covering grammars are effective in preventing catastrophic errors in neural text normalization systems. Our operation sequence model for interpretable NMT represents translation as a series of actions that modify the translation state, and can also be seen as derivation in a formal grammar.EPSRC grant EP/L027623/1 EPSRC Tier-2 capital grant EP/P020259/

Simulation framework for multigigabit applications at 60 GHz

This dissertation describes the implementation of a OFDM-based simulation framework for multigigabit applications at 60 GHz band over indoor multipath fading channels. The main goal of the framework is to provide a modular simulation tool designed for high data rate application in order to be easily adapted to a speci c standard or technology, such as 5G. The performance of OFDM using mmWave signals is severely a ected by non-linearities of the RF front-ends. This work analyses the impact of RF impairments in an OFDM system over multipath fading channels at 60 GHz using the proposed simulation framework. The impact of those impairments is evaluated through the metrics of BER, CFR, operation range and PSNR for residential and kiosk scenarios, suggested by the standard for LOS and NLOS. The presented framework allows the employment of 16 QAM or 64 QAM modulation scheme, and the length of the cyclic pre x extension is also con gurable. In order to simulate a realistic multipath fading channel, the proposed framework allows the insertion of a channel impulse response de ned by the user. The channel estimation can be performed either using pilot subcarriers or Golay sequence as channel estimation sequences. Independently of the channel estimation technique selected, frequency domain equalization is available through ZF approach or MMSE. The simulation framework also allows channel coding techniques in order to provide a more robustness transmission and to improve the link budget

Hazard-free clock synchronization

The growing complexity of microprocessors makes it infeasible to distribute a single clock source over the whole processor with a small clock skew. Hence, chips are split into multiple clock regions, each covered by a single clock source. This poses a problem for communication between these clock regions. Clock synchronization algorithms promise an advantage over state-of-the-art solutions, such as GALS systems. When clock regions are synchronous the communication latency improves significantly over handshake-based solutions. We focus on the implementation of clock synchronization algorithms. A major obstacle when implementing circuits on clock domain crossings are hazardous signals. We can formally define hazards by extending the Boolean logic by a third value u. In this thesis, we describe a theory for designing and analyzing hazard-free circuits. We develop strategies for hazard-free encoding and construction of hazard-free circuits from finite state machines. Furthermore, we discuss clock synchronization algorithms and a possible combination of them. In the end, we present two implementations of the GCS algorithm by Lenzen, Locher, and Wattenhofer (JACM 2010). We prove by rigorous analysis that the systems implement the algorithm. The theory described above is used to prove that our clock synchronization circuits are hazard-free (in the sense that they compute the most precise output possible). Simulation of our GCS system shows that it achieves a skew between neighboring clock regions that is smaller than a few inverter delays.Aufgrund der zunehmenden Komplexität von Mikroprozessoren ist es unmöglich, mit einer einzigen Taktquelle den gesamten Prozessor ohne großen Versatz zu takten. Daher werden Chips in mehrere Regionen aufgeteilt, die jeweils von einer einzelnen Taktquelle abgedeckt werden. Dies stellt ein Problem für die Kommunikation zwischen diesen Taktregionen dar. Algorithmen zur Taktsynchronisation bieten einen Vorteil gegenüber aktuellen Lösungen, wie z.B. GALS-Systemen. Synchronisiert man die Taktregionen, so verbessert sich die Latenz der Kommunikation erheblich. In Schaltkreisen zwischen zwei Taktregionen können undefinierte Signale, sogenannte Hazards auftreten. Indem wir die boolesche Algebra um einen dritten Wert u erweitern, können wir diese Hazards formal definieren. In dieser Arbeit zeigen wir eine Methode zum Entwurf und zur Analyse von hazard-freien Schaltungen. Wir entwickeln Strategien für Kodierungen die Hazards vermeiden und zur Konstruktion von hazard-freien Schaltungen. Darüber hinaus stellen wir Algorithmen Taktsynchronisation vor und wie diese kombiniert werden können. Zum Schluss stellen wir zwei Implementierungen des GCS-Algorithmus von Lenzen, Locher und Wattenhofer (JACM 2010) vor. Oben genannte Mechanismen werden verwendet, um formal zu beweisen, dass diese Implementierungen korrekt sind. Die Implementierung hat keine Hazards, das heißt sie berechnet die bestmo ̈gliche Ausgabe. Anschließende Simulation der GCS Implementierung erzielt einen Versatz zwischen benachbarten Taktregionen, der kleiner als ein paar Gatter-Laufzeiten ist

Index to NASA Tech Briefs, 1975

This index contains abstracts and four indexes--subject, personal author, originating Center, and Tech Brief number--for 1975 Tech Briefs

Risteämättömien verkkojen perheiden yleinen aksiomatisointi dependenssijäsentämisessä

Proceeding volume: 55We present a simple encoding for unlabeled noncrossing graphs and show how its latent counterpart helps us to represent several families of directed and undirected graphs used in syntactic and semantic parsing of natural language as context-free languages. The families are separated purely on the basis of forbidden patterns in latent encoding, eliminating the need to differentiate the families of non-crossing graphs in inference algorithms: one algorithm works for all when the search space can be controlled in parser input.We present a simple encoding for unlabeled noncrossing graphs and show how its latent counterpart helps us to represent several families of directed and undirected graphs used in syntactic and semantic parsing of natural language as context-free languages. The families are separated purely on the basis of forbidden patterns in latent encoding, eliminating the need to differentiate the families of non-crossing graphs in inference algorithms: one algorithm works for all when the search space can be controlled in parser input.Peer reviewe