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Mercury Systems Reports First Quarter Fiscal 2014 Results

Business Outlook

This section presents our current expectations and estimates, given current visibility, on our business outlook for the current fiscal quarter. It is possible that actual performance will differ materially from the estimates given, either on the upside or on the downside. Investors should consider all of the risks, with respect to these estimates, including those listed in the Safe Harbor Statement below and in our periodic filings with the U.S. Securities and Exchange Commission, and make themselves aware of the risk factors that may impact our actual performance.

For the second quarter of fiscal 2014, revenues are currently forecasted to be in the range of $48 million to $54 million. At this range, GAAP net loss per share is expected to be in the range of a net loss of $0.06 to $0.12 per share. Projected GAAP net loss per share includes $0.04 per share associated with forecasted amortization of acquired intangible assets.

Adjusted EBITDA for the second quarter of fiscal 2014 is expected to be in the range of $0.4 million to $3.5 million. 

Recent Highlights

September – Mercury announced that its Mercury Defense Systems (MDS) subsidiary received a $3.9 million initial contract award against its 5 year sole source basic ordering agreement to deliver advanced Digital RF Memory (DRFM) jammers to the U.S. Navy. The order is expected to be shipped by the end of Mercury's fiscal 2015 third quarter.

September – Mercury announced the Ensemble® HDS6602 High Density Server, the embedded computing industry's most powerful 6U OpenVPX™ processing module. The Company expects the HDS6602 to be the only embedded, dual Intel® Xeon® processor E5-2600 v2-based processing module able to deliver peak Symmetric Multi-Processing performance of 608 GLOPS. Using Mellanox's ConnectX®-3 technology to exploit InfiniBand™ or Ethernet as a high-performance interconnect in OpenVPX, the HDS6602 is well suited to meet the processing demands of the most complex radar and other massively intensive embedded processing applications.

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