11 research outputs found

    Cellular Automata Can Reduce Memory Requirements of Collective-State Computing

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    Various non-classical approaches of distributed information processing, such as neural networks, computation with Ising models, reservoir computing, vector symbolic architectures, and others, employ the principle of collective-state computing. In this type of computing, the variables relevant in a computation are superimposed into a single high-dimensional state vector, the collective-state. The variable encoding uses a fixed set of random patterns, which has to be stored and kept available during the computation. Here we show that an elementary cellular automaton with rule 90 (CA90) enables space-time tradeoff for collective-state computing models that use random dense binary representations, i.e., memory requirements can be traded off with computation running CA90. We investigate the randomization behavior of CA90, in particular, the relation between the length of the randomization period and the size of the grid, and how CA90 preserves similarity in the presence of the initialization noise. Based on these analyses we discuss how to optimize a collective-state computing model, in which CA90 expands representations on the fly from short seed patterns - rather than storing the full set of random patterns. The CA90 expansion is applied and tested in concrete scenarios using reservoir computing and vector symbolic architectures. Our experimental results show that collective-state computing with CA90 expansion performs similarly compared to traditional collective-state models, in which random patterns are generated initially by a pseudo-random number generator and then stored in a large memory.Comment: 13 pages, 11 figure

    Communicating the Unspeakable: Linguistic Phenomena in the Psychedelic Sphere

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    Psychedelics can enable a broad and paradoxical spectrum of linguistic phenomena from the unspeakability of mystical experience to the eloquence of the songs of the shaman or curandera. Interior dialogues with the Other, whether framed as the voice of the Logos, an alien download, or communion with ancestors and spirits, are relatively common. Sentient visual languages are encountered, their forms unrelated to the representation of speech in natural language writing systems. This thesis constructs a theoretical model of linguistic phenomena encountered in the psychedelic sphere for the field of altered states of consciousness research (ASCR). The model is developed from a neurophenomenological perspective, especially the work of Francisco Varela, and Michael Winkelman’s work in shamanistic ASC, which in turn builds on the biogenetic structuralism of Charles Laughlin, John McManus, and Eugene d’Aquili. Neurophenomenology relates the physical and functional organization of the brain to the subjective reports of lived experience in altered states as mutually informative, without reducing consciousness to one or the other. Consciousness is seen as a dynamic multistate process of the recursive interaction of biology and culture, thereby navigating the traditional dichotomies of objective/subjective, body/mind, and inner/outer realities that problematically characterize much of the discourse in consciousness studies. The theoretical work of Renaissance scholar Stephen Farmer on the evolution of syncretic and correlative systems and their relation to neurobiological structures provides a further framework for the exegesis of the descriptions of linguistic phenomena in first-person texts of long-term psychedelic selfexploration. Since the classification of most psychedelics as Schedule I drugs, legal research came to a halt; self-experimentation as research did not. Scientists such as Timothy Leary and John Lilly became outlaw scientists, a social aspect of the “unspeakability” of these experiences. Academic ASCR has largely side-stepped examination of the extensive literature of psychedelic selfexploration. This thesis examines aspects of both form and content from these works, focusing on those that treat linguistic phenomena, and asking what these linguistic experiences can tell us about how the psychedelic landscape is constructed, how it can be navigated, interpreted, and communicated within its own experiential field, and communicated about to make the data accessible to inter-subjective comparison and validation. The methodological core of this practice-based research is a technoetic practice as defined by artist and theoretician Roy Ascott: the exploration of consciousness through interactive, artistic, and psychoactive technologies. The iterative process of psychedelic self-exploration and creation of interactive software defines my own technoetic practice and is the means by which I examine my states of consciousness employing the multidimensional visual language Glide

    Complexity Reduction in Image-Based Breast Cancer Care

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    The diversity of malignancies of the breast requires personalized diagnostic and therapeutic decision making in a complex situation. This thesis contributes in three clinical areas: (1) For clinical diagnostic image evaluation, computer-aided detection and diagnosis of mass and non-mass lesions in breast MRI is developed. 4D texture features characterize mass lesions. For non-mass lesions, a combined detection/characterisation method utilizes the bilateral symmetry of the breast s contrast agent uptake. (2) To improve clinical workflows, a breast MRI reading paradigm is proposed, exemplified by a breast MRI reading workstation prototype. Instead of mouse and keyboard, it is operated using multi-touch gestures. The concept is extended to mammography screening, introducing efficient navigation aids. (3) Contributions to finite element modeling of breast tissue deformations tackle two clinical problems: surgery planning and the prediction of the breast deformation in a MRI biopsy device

    The Ternary Quantum-dot Cellular Automata Memorizing Cell

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    Proceedings of the 7th Sound and Music Computing Conference

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    Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010

    Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference

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