The Gulf Stream System is one of the most important components of the North Atlantic Circulation. Reciprocal acoustic transmissions have been analyzed to determine the structure and variability of temperature, current velocity, and relative vorticity in a region just south of the Gulf Stream. Observational evidence is presented that the Gulf Stream is the source of the energetic eddy variability found in the Atlantic interior. Through highly nonlinear processes, eddy activity (energy) radiates away from the Stream southward via Rossby wave packets.

Several advanced DSP algorithms, arising in applications such as wireless communications, computer graphics, computerized tomography, and speech compression, require extensive use of nonlinear functions. We discuss a new hardware approach to high-speed computation of nonlinear functions. With this approach all of the functions needed can be regularized into a single efficient algorithm. Further, highly reduced cycle implementations can be achieved. Specifically, for real arguments, a new result can be produced every cycle --in a pipelined malde. The underlying principle which has made the combined goals of high-speed and multi-finctionalily possible is significancebased polynomial interpolation of very small ROM tables. Considered are the following seven functions: arctangent, cosine, logarithm, reciprocal, reciprocal-square-root, sine, and square-root.Also presented is a theoretical development for error prediction, a tool for the selection of architectural parameters. Finally, the paper presents a novel technique, named here as 'microshaping', for avoiding overflows, thereby eliminating exception handling.

Chaotic spread spectrum communication systems provide a number of advantages for secure communications due to the apparent randomness of the underlying spreading signal. Many of these chaotic signals exhibit colored spectra, providing discernible features that enable their detection independent of the transmitted data. A recent digital chaotic circuit [1] has been shown to exhibit a truly white spectrum in addition to apparent time-domain randomness. This maximal entropy characteristic supports Shannon's criteria for maximal channel capacity communication, low probability of interception/ detection (LPI/LPD), and a compact bandlimited white spectrum. Such a signal is featureless, susceptible only by energy detection. The disadvantage of such spread communication systems, one shared equally by all spread spectrum systems, is that the channel capacity is constrained by the bandwidth increases required for spreading gain. A traditional approach to increasing bandwidth efficiency is generalizing the modulated digital signaling constellation to include multiple levels of amplitude and phase modulation, which enhances exploitable cyclostationary features unless compensated. This paper presents a framework for adapting the maximal entropy digital chaotic signal to featureless chaotic spread spectrum modulation of arbitrary discrete-time discrete-amplitude data constellations, permitting higher throughputs in chaotic spread spectrum communication systems without sacrificing any of the maximum entropy characteristics that provide LPI/LPD.

Contemporary digital communication systems such as those ABSTRACT being developed for the deployment of third-generation cellular require ever increasing performance levels in their signal processing chains to extract higher data rates and to provide decreasing price/performance ratios. Additionally, communication systems like 3G that must support multimode flexibility, such as the software radio, must be able to reconfigure their signal processing chains while keeping circuit complexity to a minimum. Given these constraints, DSP is the only viable alternative for baseband processing and digital IF processing. DSP is in many cases the only viable alternative to analog IF processing. Digital IF affords greater flexibility and higher performance in terms of attenuation and selectivity. It also offers better time and environment stability and lower equipment production costs than traditional analog techniques. opment oftware radio and digital intermediate frequency S (IF) technology are enabling the economic develof third-generation cellular base stations by providing the required flexibility and fidelity at reasonable price points. Digital signal processing (DSP) affords greater flexibility and higher performance (in terms of attenuation and selectivity) than traditional analog techniques. It also offers better stability over time and environmental parameters with lower equipment production costs. Additionally, components available today let DSP extend from baseband to intermediate frequencies. This makes DSP useful for tuning, signal selection, and frequency up-and downconversion.

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