Object detecting artificial retina

This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self-contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware.

Auto-associative memory using n-tuple techniques

The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.

Object-based three-dimensional X-ray imaging

A form of three-dimensional X-ray imaging, called Object 3-D, is introduced, where the relevant subject material is represented as discrete ‘objects’. The surface of each such object is derived accurately from the projections of its outline, and of its other discontinuities, in about ten conventional X-ray views, distributed in solid angle. This technique is suitable for many applications, and permits dramatic savings in radiation exposure and in data acquisition and manipulation. It is well matched to user-friendly interactive displays.

A Wiener model for memory high power amplifiers using B-spline function approximation

In this paper we introduce a new Wiener system modeling approach for memory high power amplifiers in communication systems using observational input/output data. By assuming that the nonlinearity in the Wiener model is mainly dependent on the input signal amplitude, the complex valued nonlinear static function is represented by two real valued B-spline curves, one for the amplitude distortion and another for the phase shift, respectively. The Gauss-Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first order derivatives recursion. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.

Autobiographical memory and the self in a case of transient epileptic amnesia

Transient epileptic amnesia (TEA) is characterized by deficits in autobiographical memory (AM). One of the functions of AM is to maintain the self, suggesting that the self may undergo changes as a result of memory loss in temporal lobe epilepsy. To examine this, we used a modification of a task used to assess the relationship between self and memory (the IAM task) in a single case, E.B. Despite complaints of AM loss, E.B. had no difficulty in producing a range of self-images (e.g., I am a husband) and collections of self-defining AMs in support of these statements. E.B. produced fewer episodic memories at times of self-formation, but this did not seem to impact on the maintenance of self. The results support recent work suggesting the self may be maintained in the absence of episodic memory. The application of tasks such as that used here will further elucidate AM impairment in temporal lobe epilepsy. (C) 2011 Elsevier Inc. All rights reserved.

Autobiographical memory and amnesia: using conceptual knowledge to ground the self

A case of retrograde amnesia, PJM, elucidated the relationship between self, episodic memory and autobiographical knowledge. Results from a variety of measures including the I Am Memory Task (IAM Task), where memories are cued by self-generated self concepts, demonstrate that PJM has a coherent, continuous sense of self, despite having lost episodic memories for an 18-month period. Her use of conceptual autobiographical knowledge, in episodic tasks and to support aspects of identity, shows how autobiographical knowledge can support the self when episodic memories are inaccessible. These results are discussed with relation to current neuropsychological models of self and memory.

Autobiographical memory, autonoetic consciousness, and identity in Asperger syndrome

Previous results from research on individuals with Asperger syndrome (AS) suggest a diminished ability for recalling episodic autobiographical memory (AM). The primary aim of this study was to explore autobiographical memory in individuals with Asperger syndrome and specifically to investigate whether memories in those with AS are characterized by fewer episodic 'remembered' events (due to a deficit in autonoetic consciousness). A further aim was to examine whether such changes in AM might also be related to changes in identity, due to the close relationship between memory and the self and to the established differences in self-referential processes in AS. Eleven adults with AS and fifteen matched comparison participants were asked to recall autobiographical memories from three lifetime periods and for each memory to give either a remember response (autonoetic consciousness) or a know response (noetic consciousness). The pattern of results shows that AS participants recalled fewer memories and that these memories were more often rated as known, compared to the comparison group. AS participants also showed differences in reported identity, generating fewer social identity statements and more abstract, trait-linked identities. The data support the view that differences in both memory and reported personal identities in AS are characterized by a lack of specificity.