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In this paper, we present the implementation of Velocity Controlled (or tuned) Oscillators (VCO) to model spatial coding and navigation in the mammalian hippocampus. Specifically, we demonstrate these spatial cells by representing a spatial firing map of grid, place, and border cells. Since the VCO is the basis for Oscillatory Interference (OI) models based on the Spatial Envelope Synthesis (SES) approach of hippocampal and entorhinal navigation, we use these models in our hardware implementation to construct more complex spatial cells from simple interference between VCOs. We develop the design of a VCO ASIC chip containing up to 128 independently tuned VCOs.

The spatial-musical association of response codes (SMARC) effect, in which a high-pitched (low-pitched) tone facilitates an upper (lower) response, is considered to reflect the spatial coding of sound pitch. However, previous studies have not excluded the directional effects of sound localization. Because a high-pitched (low-pitched) tone is automatically misperceived as originating from a spatially high (low) location, the location of a perceived sound source might artificially elicit the SMARC effect. This study challenged this issue, by demonstrating whether the SMARC effect occurs in response to sound imagery without sound input. To achieve this goal, participants were first trained to associate visual stimuli (novel contoured shapes) with sound pitches (high-pitched or low-pitched pure tones). Subsequently, they elicited the SMARC effect for trained visual stimuli (novel contoured shapes) associated with pitch height. Therefore, the SMARC effect was observed without sound localization but with the activation of sound imagery that was spatial.

The paper dwells on the modified model of the wireless data transmission channel based on the well-known standard 3rd Generation Partnership Project. Besides, for the suggested channel model there has been performed an adaptive algorithm simulation in the wireless communication system basing on the spatial coding. The paper discusses use of an adaptive algorithm in simulation a communication system with the proposed channel model. The adaptation consists in the adaptively formation of the directional pattern receiving antenna according.

This paper presents the design and fabrication of a Compressive Reflector Antenna (CRA)for high-sensing-capacity millimeter-wave imaging applications. The CRA is fabricated using additive manufacturing or 3D printing and metalized by applying silver conductive coating spray on its surface. The near-fields of the CRA are measured when it is fed by a conical horn antenna, a compressive horn antenna, and a perturbed cavity. The singular value distribution and sensing capacity of the CRA fed by the aforementioned antennas are calculated and compared.

Metamaterials are artificial structures composed of subwavelength unit cells to control electromagnetic (EM) waves. The coding representation of metamaterial has the ability to describe the material in a digital way. Recently the concept of frequency coding metamaterials were proposed, in which the metamaterials were typically constructed by unit cells which achieves different controls of EM energy radiations with a fixed spatial coding pattern when the frequency changes. In this case, not only different phase responses of the unit cells are considered, different phase sensitivities are also required. Due to the different frequency sensitivities of unit cells, units with the same phase response at the initial frequency may have different phase responses at the higher frequency. By using units with different sensitivities, multiple predesigned functions can be realized by the frequency coding metamaterial without changing the coding sequence. Here we use frequency coding method to design a reflection-type antenna, which can realize predesigned frequency sweeping in the working spectra.

Hierarchical Predictive Coding systems that have adopted prediction as their primary goal, are heavily reliant on the stable sparse coding of sensory input. Furthermore, such systems will require their spatial coding function to be adaptive and able to reform to reflect changes within the environment. These properties of stability and adaptiveness should emerge naturally from the spatial coding system and not be reliant on additional control mechanisms. Hierarchical Temporal Memory is a cortically inspired model that encapsulates both sparse coding and temporal processing functions. We present an investigation into the stability and adaptiveness of three alternative versions of the spatial pooling function. Our results show that two of these SP algorithms are able to form stable sparse distributed representations of audio input, while still remaining adaptive to changes within the input data.

We have examined the characteristics of neural noise in amblyopia, a disorder that impairs binocular vision. Non-invasive methods based on signal-detection theory and psychophysics were used to measure threshold fluctuations in orientation processing, which is considered a main feature of cortical processing. Fluctuations were correlated and increase with the response size by power law scaling behavior. The scaling exponent in amblyopia was similar or lower than normal vision. Comparisons between observational conditions have revealed that the scaling exponent in normal binocular vision was lower than the monocular case. Surprisingly, the exponents in the amblyopic and fellow eye were lower than in amblyopic vision. The results conclude that amblyopia does not necessarily involve greater internal noise but an inverted trend.

In this contribution, spatial coding diversity is combined with spatial multiplexing to get higher joint gains on ensuring both low error rate and high spectrum efficiency. A general mathematical model of joint spatial coding and multiplexing (JSCM) is proposed and analyzed. Optimal criteria and a suboptimal iterative algorithm on the design of JSCM are studied. Performance of JSCM is proved by simulations from various aspects.