Implementation of bio-inspired adaptive wavelet transforms in FPGAs. Modeling, validation and profiling of the algorithm

Providing embedded systems with adaptation capabilities is an increasing importance objective in design community. This work deals with the implementation of adaptive compression schemes in FPGA devices by means of a bioinspired algorithm. A simplified version of an Evolution Strategy using fixed point arithmetic is proposed. Specifically, a simpler than the standard (hardware friendly) mutation operator is designed, modelled and validated using a high-level language. HW/SW partitioning issues are considered and code profiling accomplished to validate the proposal. Preliminary results of the proposed hardware architecture are also show

Evolutionary design and optimization of Wavelet Transforms for image compression in embedded systems

This paper describes the initial studies of an Evolution Strategy aimed at implementation on embedded systems for the evolution of Wavelet Transforms for image compression. Previous works in the literature have already been proved useful for this application, but they are highly computationally intensive. Therefore, the work described here, deals with the simplifications made to those algorithms to reduce their computing requirements. Several optimizations have been done in the evaluation phase and in the EA operators. The results presented show how the proposed algorithm cut outs still allow for good results to be achieved, while effectively reducing the computing requirements

Evolutionary Approach to Improve Wavelet Transforms for Image Compression in Embedded Systems

A bioinspired, evolutionary algorithm for optimizing wavelet transforms oriented to improve image compression in embedded systems is proposed, modelled, and validated here. A simplified version of an Evolution Strategy, using fixed point arithmetic and a hardware-friendly mutation operator, has been chosen as the search algorithm. Several cutdowns on the computing requirements have been done to the original algorithm, adapting it for an FPGA implementation. The work presented in this paper describes the algorithm as well as the test strategy developed to validate it, showing several results in the effort to find a suitable set of parameters that assure the success in the evolutionary search. The results show how high-quality transforms are evolved from scratch with limited precision arithmetic and a simplified algorithm. Since the intended deployment platform is an FPGA, HW/SW partitioning issues are also considered as well as code profiling accomplished to validate the proposal, showing some preliminary results of the proposed hardware architecture

Bio-inspired FPGA Architecture for Self-Calibration of an Image Compression Core based on Wavelet Transforms in Embedded Systems

A generic bio-inspired adaptive architecture for image compression suitable to be implemented in embedded systems is presented. The architecture allows the system to be tuned during its calibration phase. An evolutionary algorithm is responsible of making the system evolve towards the required performance. A prototype has been implemented in a Xilinx Virtex-5 FPGA featuring an adaptive wavelet transform core directed at improving image compression for specific types of images. An Evolution Strategy has been chosen as the search algorithm and its typical genetic operators adapted to allow for a hardware friendly implementation. HW/SW partitioning issues are also considered after a high level description of the algorithm is profiled which validates the proposed resource allocation in the device fabric. To check the robustness of the system and its adaptation capabilities, different types of images have been selected as validation patterns. A direct application of such a system is its deployment in an unknown environment during design time, letting the calibration phase adjust the system parameters so that it performs efcient image compression. Also, this prototype implementation may serve as an accelerator for the automatic design of evolved transform coefficients which are later on synthesized and implemented in a non-adaptive system in the final implementation device, whether it is a HW or SW based computing device. The architecture has been built in a modular way so that it can be easily extended to adapt other types of image processing cores. Details on this pluggable component point of view are also given in the paper

Accelerating FPGA-based evolution of wavelet transform filters by optimized task scheduling

Adaptive embedded systems are required in various applications. This work addresses these needs in the area of adaptive image compression in FPGA devices. A simplified version of an evolution strategy is utilized to optimize wavelet filters of a Discrete Wavelet Transform algorithm. We propose an adaptive image compression system in FPGA where optimized memory architecture, parallel processing and optimized task scheduling allow reducing the time of evolution. The proposed solution has been extensively evaluated in terms of the quality of compression as well as the processing time. The proposed architecture reduces the time of evolution by 44% compared to our previous reports while maintaining the quality of compression unchanged with respect to existing implementations. The system is able to find an optimized set of wavelet filters in less than 2 min whenever the input type of data changes

Nitrene-carbene-carbene rearrangement. photolysis and thermolysis of tetrazolo[5,1- a ]phthalazine with formation of 1-phthalazinylnitrene, o-cyanophenylcarbene, and phenylcyanocarbene

1-Azidophthalazine 9A is generated in trace amount by mild FVT of tetrazolo[5,1-a]phthalazine 9T and is observable by its absorption at 2121 cm-1 in the Ar matrix IR spectrum. Ar matrix photolysis of 9T/9A at 254 nm causes ring opening to generate two conformers of (o-cyanophenyl) diazomethane 11 (2079 and 2075 cm-1), followed by (o-cyanophenyl)carbene 312, cyanocycloheptatetraene 13, and finally cyano(phenyl)carbene 314 as evaluated by IR spectroscopy. The two carbenes 312 and 314 were observed by ESR spectroscopy (D|hc = 0.5078, E|hc = 0.0236 and D|hc = 0.6488, E|hc = 0.0195 cm-1, respectively). The rearrangement of 12 â., 13 â., 14 constitutes a carbene-carbene rearrangement. 1-Phthalazinylnitrene 310 is observed by means of its UV-vis spectrum in Ar matrix following FVT of 9 above 550 C. Rearrangement to cyanophenylcarbenes also takes place on FVT of 9 as evidenced by observation of the products of ring contraction, viz., fulvenallenes and ethynylcyclopentadienes 16-18. Thus the overall rearrangement 10 → 11 → 12 â., 13 â., 14 can be formulated

Minds & Machines DOI 10.1007/s11023-007-9071-5 Evolved Computing Devices and the Implementation Problem

Abstract The evolutionary circuit design is an approach allowing engineers to realize computational devices. The evolved computational devices represent a distinctive class of devices that exhibits a specific combination of properties, not visible and studied in the scope of all computational devices up till now. Devices that belong to this class show the required behavior; however, in general, we do not understand how and why they perform the required computation. The reason is that the evolution can utilize, in addition to the ‘‘understandable composition of elementary components’’, material-dependent constructions and properties of environment (such as temperature, electromagnetic field etc.) and, furthermore, unknown physical behaviors to establish the required functionality. Therefore, nothing is known about the mapping between an abstract computational model and its physical implementation. The standard notion of computation and implementation developed in computer science as well as in cognitive science has become very problematic with the existence of evolved computational devices. According to the common understanding, the evolved devices cannot be classified as computing mechanisms

Role of glutamate receptors in transmission of vagal cardiac input to neurones in the nucleus tractus solitarii in dogs

Vagal afferent input from cardiac mechanoreceptors excites neurones in the nucleus tractus solitarii (NTS), but discharge patterns evoked by physiological activation of pressure-sensitive cardiac mechanoreceptors have not been studied in vivo. The role of glutamate receptor subtypes in transmission of afferent activity to the NTS neurones has not been determined. The present study therefore has two aims: first, to characterise the discharge patterns of neurones in the NTS that receive pressure-sensitive vagal cardiac receptor input and second, to determine the roles of ionotropic glutamate receptor subtypes in the transmission of this putative cardiac mechanoreceptor-related activity to NTS neurones.Pulse-synchronous activity of neurones in the NTS evoked by vagal afferent input was recorded extracellularly in an anaesthetised dog model using multibarrel glass electrodes, which allowed picoejection of the glutamate receptor antagonists NBQX or AP5 to block either non-NMDA or NMDA receptors, respectively, during the neuronal recording. Pressure sensitivity of the recorded neurones was examined by monitoring their response to a small increase in arterial blood pressure. Selective pressure activation of carotid sinus baroreceptors in an isolated sinus or selective denervation of aortic baroreceptors were used to test for convergent excitation of the neurones by arterial baroreceptors.Pulse-synchronous cardiac-related neuronal activity recorded from neurones in both the right and left NTS was eliminated following section of the left (n = 17) or right (n = 1) vagus nerves. No spontaneous, non-pulsatile activity was observed in these neurones before or after vagotomy. Activity transmitted via left vagal afferents was found to be sensitive to changes in arterial blood pressure. In these neurones, activity was blocked in 13 of 17 neurones by picoejection of NBQX, with the remainder requiring both NBQX and AP5. None of the cardiac-related neurones responded to activation of carotid baroreceptors or denervation of aortic baroreceptors, indicating no convergence of activity from carotid baroreceptors or aortic baroreceptors with pressure thresholds of approximately 130 mmHg or less.The results suggest that vagal pressure-sensitive afferent input from cardiac mechanoreceptors is transmitted primarily by left vagal afferent fibres via non-NMDA receptors to neurones in both the ipsilateral and contralateral NTS. NMDA receptors were also found to have a role in the activation of a small subpopulation of neurones